To see the other types of publications on this topic, follow the link: Dutch Network of Operations Research.
Dissertations / Theses on the topic 'Dutch Network of Operations Research'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Dutch Network of Operations Research.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Vohnout, Sonia Isabel 1964. "Diverse routing in network planning." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/291952.
Full textAbstract:
This thesis discusses an algorithm and two heuristics for solving a particular network optimization problem: The node-disjoint paths problem. The goal of this optimization problem is to find two node-disjoint paths between a given origin-destination pair whose total cost is minimum. This problem is shown to be NP-Hard. Two heuristics are investigated in this thesis. The sequential shortest paths heuristic, is the faster of the two methods, but the quality of the solution may be sacrificed. On the other hand, the simultaneous shortest paths heuristic, which yields very good solutions, has higher complexity. We also discuss an implicit enumeration algorithm that is used to verify the quality of the solution obtained from the heuristics.
2
Hui, Kin-Ping. "Network reliability estimation." Title page, table of contents and abstract only, 2005. http://hdl.handle.net/2440/37952.
Full textAbstract:
Computing the reliability of a network is a #P-complete problem, therefore estimation by means of simulation often becomes a favourable choice. In modern communication networks, link failure probabilities are usually small and hence network failures become rare events. This poses a challenge to estimate the network reliability. In this thesis we present different techniques for network reliability estimation. There are two main sampling techniques in reliability estimation: combinatorial and permutational sampling. Combinatorial sampling has the advantage of speed but has poor performance in rare event simulations. Permutational sampling gives good simulation performance but at a higher computational cost. We combine the two techniques and propose a hybrid sampling scheme called Tree Cut and Merge. By employing simple bounding together with clever conditional sampling, the TCM scheme achieves over 10(superscript 7) times speed up in certain classes of heterogeneous networks. The Crude Monte Carlo (combinatorial) component in the Tree Cut and Merge scheme may cause problems in some situations. In bad cases, the slow convergence problem re-appears. To address the problem, we modifed the scheme by introducing the Importance Sampling technique. The new Tree Cut and Merge with Importance Sampling scheme maintained the speed advantage of the Tree Cut and Merge and minimizes, at the same time, the potential problems caused by the Crude Monte Carlo component. Associated with the Importance Sampling technique, a new technique called the Cross-Entropy method has been developed in the late 90's to find the optimal Importance Sampling parameters. By employing the Cross-Entropy technique, we propose a new scheme called the Merge Process with Cross-Entropy. The new scheme improves the Merge Process in nearly all classes of network; in contrast, Tree Cut and Merge with Importance Sampling scheme sees the greatest improvement in heterogeneous networks. Besides estimating the reliability of a single network, this thesis also investigates a closely related problem: estimating the difference in reliability of two very similar networks. The problem is closely linked to the applications in the areas of network optimization, network evolution, reconfiguration and recovery, for example. The fact that the probabilities of rare events are hard to estimate makes estimating their difference even more difficult. Coupled and differential sampling techniques are proposed and applied to various schemes in this thesis. They prove to be superior to the conventional independent "estimate and subtract" method. Interestingly, these concepts also lead to new ideas regarding the estimation of the reliability of networks that are similar to networks with polynomially computable reliability.<br>Thesis (Ph.D.)--School of Mathematical Sciences, 2005.
3
Kramer, Jeremy Daniel. "Min-Cost Multicommodity Network Flows: A Linear Case for the Convergence and Reoptimization of Multiple Single-Commodity Network Flows." NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-04242009-204158/.
Full textAbstract:
Network Flow problems are prevalent in Operations Research, Computer Science, Industrial Engineering and Management Science. They constitute a class of problems that are frequently faced by real world applications, including transportation, telecommunications, production planning, etc. While many problems can be modeled as Network Flows, these problems can quickly become unwieldy in size and difficult to solve. One particularly large instance is the Min-Cost Multicommodity Network Flow problem. Due to the time-sensitive nature of the industry, faster algorithms are always desired: recent advances in decomposition methods may provide a remedy. One area of improvement is the cost reoptimization of the min-cost single commodity network flow subproblems that arise from the decomposition. Since similar single commodity network flow problems are solved, information from the previous solution provides a "warm-start" of the current solution. While certain single commodity network flow algorithms may be faster "from scratch," the goal is to reduce the overall time of computation. Reoptimization is the key to this endeavor. Three single commodity network flow algorithms, namely, cost scaling, network simplex and relaxation, will be examined. They are known to reoptimize well. The overall goal is to analyze the effectiveness of this approach within one particular class of network problems.
4
Stier, Moses Nicolás E. "Selfish versus coordinated routing in network games." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/16650.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.<br>Includes bibliographical references (p. 159-170) and index.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>A common assumption in network optimization models is that a central authority controls the whole system. However, in some applications there are independent users, and assuming that they will follow directions given by an authority is not realistic. Individuals will only accept directives if they are in their own interest or if there are incentives that encourage them to do so. Actually, it would be much easier to let users make their own decisions hoping that the outcome will be close to the authority's goals. Our main contribution is to show that, in static networks subject to congestion, users' selfish decisions drive the system close to optimality with respect to various common objectives. This connection to individual decision making proves fruitful; not only does it provide us with insights and additional understanding of network problems, but it also allows us to design approximation algorithms for computationally difficult problems. More specifically, the conflicting objectives of the users prompt the definition of a network game in which they minimize their own latencies. We show that the so-called price of anarchy is small in a quite general setting. Namely, for networks with side constraints and non-convex, non-differentiable, and even discontinuous latency functions, we show that although an arbitrary equilibrium need not be efficient, the total latency of the best equilibrium is close to that of an optimal solution. In addition, when the measure of the solution quality is the maximum latency, equilibria in networks without constraints are also near-optimal. We provide the first analysis of the problem of minimizing that objective in static networks with congestion.<br>(cont.) As this problem is NP-hard, computing an equilibrium represents a constant-factor approximation algorithm. In some situations, the network authority might still want to do better than in equilibrium. We propose to use a solution that minimizes the total latency, subject to constraints designed to improve the solution's fairness. For several real-world instances, we compute traffic assignments of notably smaller total latency than an equilibrium, yet of similar fairness. Furthermore, we provide theoretical results that explain the conclusions derived from the computational study.<br>by Nicolás E. Stier-Moses.<br>Ph.D.
5
Lesnaia, Ekaterina. "Optimizing safety stock placement in general network supply chains." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28856.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.<br>Includes bibliographical references (p. 207-214).<br>The amount of safety stock to hold at each stage in a supply chain is an important problem for a manufacturing company that faces uncertain demand and needs to provide a high level of service to its customers. The amount of stock held should be small to minimize holding and storage costs while retaining the ability to serve customers on time and satisfy most, if not all, of the demand. This thesis analyzes this problem by utilizing the framework of deterministic service time models and provides an algorithm for safety stock placement in general-network supply chains. We first show that the general problem is NP-hard. Next, we develop several conditions that characterize an optimal solution of the general-network problem. We find that we can identify all possible candidates for the optimal service times for a stage by constructing paths from the stage to each other stage in the supply chain. We use this construct, namely these paths, as the basis for a branch and bound algorithm for the general-network problem. To generate the lower bounds, we create and solve a spanning-tree relaxation of the general-network problem. We provide a polynomial algorithm to solve these spanning tree problems. We perform a set of computational experiments to assess the performance of the general-network algorithm and to determine how to set various parameters for the algorithm. In addition to the general network case, we consider two-layer network problems. We develop a specialized branch and bound algorithm for these problems and show computationally that it is more efficient than the general-network algorithm applied to the two-layer networks.<br>by Ekaterina Lesnaia.<br>Ph.D.
6
Olsson, Eric J. "Literature survey on network concepts and measures to support research in network-centric operations." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FOlsson.pdf.
Full text
7
Meyers, Carol Ph D. Massachusetts Institute of Technology. "Network flow problems and congestion games : complexity and approximation results." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35919.
Full textAbstract:
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.<br>Includes bibliographical references (p. 155-164).<br>(cont.) We first address the complexity of finding an optimal minimum cost solution to a congestion game. We consider both network and general congestion games, and we examine several variants of the problem concerning the structure of the game and its associated cost functions. Many of the problem variants are NP-hard, though we do identify several versions of the games that are solvable in polynomial time. We then investigate existence and the price of anarchy of pure Nash equilibria in k-splittable congestion games with linear costs. A k-splittable congestion game is one in which each player may split its flow on at most k different paths. We identify conditions for the existence of equilibria by providing a series of potential functions. For the price of anarchy, we show an asymptotic lower bound of 2.4 for unweighted k-splittable congestion games and 2.401 for weighted k-splittable congestion games, and an upper bound of 2.618 in both cases.<br>In this thesis we examine four network flow problems arising in the study of transportation, communication, and water networks. The first of these problems is the Integer Equal Flow problem, a network flow variant in which some arcs are restricted to carry equal amounts of flow. Our main contribution is that this problem is not approximable within a factor of 2n(1-epsilon]), for any fixed [epsilon] > 0, where n is the number of nodes in the graph. We extend this result to a number of variants on the size and structure of the arc sets. We next study the Pup Matching problem, a truck routing problem where two commodities ('pups') traversing an arc together in the network incur the arc cost only once. We propose a tighter integer programming formulation for this problem, and we address practical problems that arise with implementing such integer programming solutions. Additionally, we provide approximation and exact algorithms for special cases of the problem where the number of pups is fixed or the total cost in the network is bounded. Our final two problems are on the topic of congestion games, which were introduced in the area of communications networks.<br>by Carol Meyers.<br>Ph.D.
8
Dimaki, Georgia. "Dynamic node clustering in hierarchical optical data center network architectures." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/128973.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, September, 2020<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 127-134).<br>During the past decade an increasing trend in the Data Center Network's traffic has been observed. This traffic is characterized mostly by many small bursty flows (mice) that last for less than few milliseconds as well as a few heavier more persistent (elephant) flows between certain number of nodes. As a result many relatively underutilized network links become momentarily hotspots with increased chance of packet loss. A potential solution could be given by Reconfigurable Optical Data Centers, due to higher traffic aggregation links and topology adaptation capabilities. An example is a novel two level hierarchical WDM-Based scalable Data Center Network architecture, RHODA, which is based on the interconnection of high speed equal sized clusters of Racks. We study the traffic based dynamic cluster membership reconfiguration of the Racks. Main goal is to maintain a near optimal network operation with respect to minimization of the inter cluster traffic, while emphasising better link utilization and network scalability. We present four algorithms, two deterministic greedy and two stochastic iterative, and discuss the tradeoffs of their use. Our results draw two main conclusion: 1) Stochastic iterative algorithms are more suitable for dynamic traffic based reconfiguration 2) Fast algorithmic deployments come at a price of reduced optimality<br>by Georgia Dimaki.<br>S.M.<br>S.M. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center
9
Burgos, Fuentes Sergio Armando. "Evaluation and redesign of a company's distribution network." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1062.
Full textAbstract:
The current Record of Study presents the qualitative and quantitative analysis of a company's network of distribution centers with the purpose of determining the convenience and the feasibility to reconfigure such a network. The study was performed with a multidisciplinary team of people within and outside of the organization. The distribution network was modeled in various forms and different solutions were obtained as new information was gathered from questionnaires, from observation and from the company's databases. Finally a recommendation was formulated to modify the current configuration of the distribution network and the feasibility to implement the suggested solution in practice was evaluated.
10
Pariazar, Mahmood. "Designing a Robust Supply Chain Network Against Disruptions." Thesis, University of Missouri - Columbia, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13877160.
Full textAbstract:
<p> Supply chains are vulnerable to disruptions at any stage of the distribution system. These disruptions can be caused by natural disasters, production problems, or labor defects. The consequences of these disruptions may result in significant economic losses or even human deaths. Therefore, it is important to consider any disruption as an important factor in strategic supply chain design. Consequently, the primary outputs of this dissertation include insights for designing robust supply chains that are neither significantly nor adversely impacted by disruptions.</p><p> The impact of correlated supplier failures is examined and how this problem can be modeled as a variant of a facility location problem is described. Two main problems are defined, the first being the design of a robust supply chain, and the second being the optimization of operational inspection schedules to maintain the quality of an already established supply chain. In this regard, both strategic and operational decisions are considered in the model and (1) a two-stage stochastic programming model; (2) a multi-objective stochastic programming model; and (3) a dynamic programming model are developed to explore the tradeoffs between cost and risk.</p><p> Three methods are developed to identify optimal and robust solutions: an integer L-shaped method; a hybrid genetic algorithm using Data Envelopment Analysis; and an approximate dynamic programming method. Several sensitivity analyses are performed on the model to see how the model output would be affected by uncertainty.</p><p> The findings from this dissertation will be able to help both practitioners designing supply chains, as well as policy makers who need to understand the impact of different disruption mitigation strategies on cost and risk in the supply chain.</p><p>
11
Maye, P. J. "Exact and heuristic methods of finding network structure in linear programs." Thesis, Coventry University, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276165.
Full text
12
Morse, Steven T. "Persistent cascades and the structure of influence in a communication network." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112009.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 90-95).<br>We present work in identifying, modeling, and predicting the structure of influence in a communication network. We focus on cellular phone data, which provides a near-global population sample (in contrast to the relatively limited scope of social media and other internet-based datasets) at the expense of losing any knowledge of the content of the communications themselves. First, using inexact tree matching and hierarchical clustering, we propose a novel method for extracting persistent patterns of communication among individuals, which we term persistent cascades. We find the cascades are short in duration ('bursty'), exhibit habitual hierarchy and long-term persistence, and reveal new roles in weekday vs. weekend spreading. We show that the persistent cascades in the data are significantly different than what is found in a random network, which we illustrate both analytically and through simulation. We show that persistent cascade membership increases the likelihood of receiving information spreading through the network, even after controlling for overall call activity. Finally, we show that the method is extensible to other communication datasets by applying it to an email dataset. In this case study, we find our approach correctly identifies key individuals, ignores noise, and identifies several interesting email chains. Second, we propose a probabilistic model for the influence structure of a network, based on a multivariate stochastic process called a Hawkes process. We develop a novel approach for parameter estimation in this model that uses a Bayesian expectation-maximization (EM) scheme with a network prior. We first apply the model in the univariate case to the group conversations identified using the persistent cascades methodology. We find that the model performs well as a predictor, and also that the estimated parameter values reveal two types of persistent cascades: low-activity conversations with high temporal clustering, and high activity conversations with moderate temporal clustering. We then apply the model in the multivariate case to samples of the cell phone data, finding that the resulting estimate of the influence matrix extends our findings with the persistent cascades.<br>by Steven T. Morse.<br>S.M.
13
Hung, Benjamin W. K. (Benjamin Wei Kit). "Optimization-based selection of influential agents in a rural Afghan social network." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61193.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 177-185).<br>This work considers the nonlethal targeting assignment problem in counterinsurgency in Afghanistan, the problem of deciding on the people whom US forces should engage through outreach, negotiations, meetings, and other interactions in order to ultimately win the support of the population in their area of operations. We developed three models: 1) the Afghan COIN social influence model, to represent how attitudes of local leaders are affected by repeated interactions with other local leaders, insurgents, and counter-insurgents, 2) the network generation model, to arrive at a reasonable representation of a Pashtun district-level, opinion leader social network, and 3) the nonlethal targeting model, a nonlinear programming (NLP) optimization formulation that identifies the k US agent assignment strategy producing the greatest arithmetic mean of the expected long-term attitude of the population. We demonstrate in experiments the merits of the optimization model in nonlethal targeting, which performs significantly better than both doctrine-based and random methods of assignment in a large network.<br>by Benjamin W. K. Hung.<br>S.M.
14
Varol, Nebibe 1980. "Inventory deployment and market area segmentation in a two-echelon distribution network design." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/17728.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.<br>Includes bibliographical references (p. 125-128).<br>Most of the logistics systems involve a multi-level distribution system structure due to value added by a multi-level configuration. Interactions of these levels, i.e. echelons, should be considered while making strategic decisions regarding the choice of the size, number and location of stocking sites as well as the tactical decision regarding the choice of inventory policy to be used. We analyze a two-echelon distribution network to characterize the market segmentation of each echelon and inventory deployment between the two-levels. Allocation of stock under a stochastic demand structure is considered simultaneously with warehousing and transportation decisions, which is an extension of the General Optimal Market Area (GOMA) Model developed by Erlenkotter. The distribution of inventory is investigated under different stock policies and the sensitivity of this distribution to various system parameters is analyzed.<br>by Nebibe Varol.<br>S.M.
15
Fast, Shannon M. (Shannon Marie). "Pandemic panic : a network-based approach to predicting social response during a disease outbreak." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91406.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2014.<br>85<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 99-104).<br>Epidemic trajectories and associated social responses vary widely between populations, with severe reactions sometimes observed. When confronted with fatal or novel pathogens, people exhibit a variety of behaviors from anxiety to hoarding of medical supplies, overwhelming medical infrastructure and rioting. We developed a coupled network approach to understanding and predicting social response to disease spread. We couple the disease spread and panic spread processes and model them through local interactions between agents. The behavioral contagion process depends on the prevalence of the disease, its perceived risk and a global media signal. We verify the model by analyzing the spread of disease and social response during the 2009 H1N1 outbreak in Mexico City, the 2003 SARS and 2009 H1N1 outbreaks in Hong Kong and the 2012-2013 Boston influenza season, accurately predicting population-level behavior. The effect of interventions on the disease spread and social response is explored, and we implement an optimization study to determine the least cost intervention, taking into account the costs of the disease itself, the intervention and the social response. We show that the optimal strategy is dependent upon the relative costs assigned to infection with the disease, intervention and social response, as well as the perceived risk of infection. This kind of empirically validated model is critical to exploring strategies for public health intervention, increasing our ability to anticipate the response to infectious disease outbreaks.<br>by Shannon M. Fast.<br>S.M.
16
Kim, Louis Y. (Louis Yongchul). "Estimating network structure and propagation dynamics for an infectious disease : towards effective vaccine allocation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91397.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2014.<br>76<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 67-72).<br>In the event of a pandemic influenza outbreak, such as the 2009-2010 H1N1 "Swine Flu" episode, it is crucial to effectively allocate limited resources in order to minimize the casualties. Design of effective resource allocation strategies requires good understanding of the underlying contact network and of the propagation dynamics. In this thesis we develop a parameter estimation method that learns the network structure, among a family of graphs, and disease dynamics from the recorded infection curve, assuming that the disease dynamics follow an SIR process. We apply the method to data collected during the 2009-2010 H1N1 epidemic and show that the best-fit model, among a scale-free network and a small-world network, indicates the scale-free network. Given the knowledge of the network structure we evaluate different vaccination strategies. As a benchmark, we allow the vaccination decisions to depend on the state of the epidemic and we show that random vaccination (which is the current practice), does not efficiently halt the spread of influenza. Instead, we propose vaccine allocation strategies that exploit the underlying network structure and provide a reduction in the number of infections by over 6 times compared to the current practice. In addition, more realistic scenario involves random encounters between agents. To test this hypothesis, we introduced a dynamic network formation on top of the static network model. We apply the estimation method to the dynamic network model and show a small improvement in estimating the infection dynamics of the 2009-2010 H1N1 influenza.<br>by Louis Y. Kim.<br>S.M.
17
Emschwiller, Matt V. "Understanding neural network sample complexity and interpretable convergence-guaranteed deep learning with polynomial regression." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127290.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, May, 2020<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 83-89).<br>We first study the sample complexity of one-layer neural networks, namely the number of examples that are needed in the training set for such models to be able to learn meaningful information out-of-sample. We empirically derive quantitative relationships between the sample complexity and the parameters of the network, such as its input dimension and its width. Then, we introduce polynomial regression as a proxy for neural networks through a polynomial approximation of their activation function. This method operates in the lifted space of tensor products of input variables, and is trained by simply optimizing a standard least squares objective in this space. We study the scalability of polynomial regression, and are able to design a bagging-type algorithm to successfully train it. The method achieves competitive accuracy on simple image datasets while being more simple. We also demonstrate that it is more robust and more interpretable that existing approaches. It also offers more convergence guarantees during training. Finally, we empirically show that the widely-used Stochastic Gradient Descent algorithm makes the weights of the trained neural networks converge to the optimal polynomial regression weights.<br>by Matt V. Emschwiller.<br>S.M.<br>S.M. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center
18
Unsal, Omur. "Two-person zero-sum network-interdiction game with multiple inspector types." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun%5FUnsal.pdf.
Full textAbstract:
Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2010.<br>Thesis Advisor(s): Wood, R. Kevin ; Second Reader: Salmeron, Javier. "June 2010." Description based on title screen as viewed on July 14, 2010. Author(s) subject terms: Two-person zero-sum network-interdiction game, game theoretic network interdiction, column generation, pure inspection-assignment strategy, inspector-to-edge assignment and mixed strategies, marginal probability, Cournet's simultaneous play game. Includes bibliographical references (p. 47-48). Also available in print.
19
McPherson, Deanne B. "A contrasting look at network formation models and their application to the minimum spanning tree." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Sep/09Sep%5FMcPherson.pdf.
Full textAbstract:
Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2009.<br>Thesis Advisor(s): Alderson, David L. "September 2009." Description based on title screen as viewed on November 5, 2009. Author(s) subject terms: Network formation, graph generation, minimum spanning tree, price of anarchy. Includes bibliographical references (p. 43-45). Also available in print.
20
Sanchez, Aaron. "Internet service provider network evolution in the presence of changing environmental conditions." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Mar/10Mar%5FSanchez.pdf.
Full textAbstract:
Thesis (M.S. in Operations Research)--Naval Postgraduate School, March 2010.<br>Thesis Advisor(s): Alderson, David L. Second Reader: Carlyle, W. Matthew. "March 2010." Description based on title screen as viewed on April 23, 2010. Author(s) subject terms: Internet Service Provider, traffic engineering, network provisioning, network design, network topology, demand matrices Includes bibliographical references (p. 87-89). Also available in print.
21
Solveson, Keith D. "Design and implementation of a Primal Simplex Network Optimizer in C." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA241350.
Full textAbstract:
Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990.<br>Thesis Advisor(s): Bradley, Gordon H. Second Reader: Stemp, Roger. "September 1990." Description based on title screen as viewed on December 21, 2009. DTIC Descriptor(s): Computer Networks, Simplex Method, Computer Program Documentation, Optimization, Programming Languages, Theses, Time, FORTRAN, Tuning, Symbols, Parameters, Networks, Algorithms, Test And Evaluation, Data Bases. DTIC Identifier(s): Software Engineering. Author(s) subject terms: Network, C, Primal, Transportation, Transshipment, Simplex. Includes bibliographical references (p. 48-50). Also available in print.
22
Johnstone, Daniel P. "Integrated retrograde, repair scheduling, and distribution policies in a multi-echelon service parts supply network with multiple repair depots." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3380089.
Full textAbstract:
Thesis (Ph.D.)--Indiana University, Kelley School of Business, 2009.<br>Title from PDF t.p. (viewed on Jul 19, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: B, page: 7834. Adviser: S. Christian Albright.
23
Marla, Lavanya. "Robust optimization for network-based resource allocation problems under uncertainty." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39280.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2007.<br>Includes bibliographical references (p. 129-131).<br>We consider large-scale, network-based, resource allocation problems under uncertainty, with specific focus on the class of problems referred to as multi-commodity flow problems with time-windows. These problems are at the core of many network-based resource allocation problems. Inherent data uncertainty in the problem guarantees that deterministic optimal solutions are rarely, if ever, executed. Our work examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we can generate solutions that are more robust operationally, that is, more likely to be executed or easier to repair when disrupted. The challenges are the following: approaches to achieve robustness 1) can be extremely problem-specific and not general; 2) suffer from issues of tractability; or 3) have unrealistic data requirements. We propose in this work a modeling and algorithmic framework that addresses the above challenges.<br>(cont.) Our modeling framework involves a decomposition scheme that separates problems involving multi-commodity flows with time-windows into routing (that is, a routing master problem) and scheduling modules (that is, a scheduling sub-problem), and uses an iterative scheme to provide feedback between the two modules, both of which are more tractable than the integrated model. The master problem has the structure of a multi-commodity flow problem and the sub-problem is a set of network flow problems. This decomposition allows us to capture uncertainty while maintaining tractability. Uncertainty is captured in part by the master problem and in part by the sub-problem. In addition to solving problems under uncertainty, our decomposition scheme can also be used to solve large-scale resource allocation problems without uncertainty. As proof-of-concept, we apply our approach to a vehicle routing and scheduling problem and compare its solutions to those of other robust optimization approaches. Finally, we propose a framework to extend our robust, decomposition approach to the more complex problem of network design.<br>by Lavanya Marla.<br>S.M.
24
Koc, Levent. "Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection." The George Washington University, 2013.
Find full text
25
Ghamasaee, Rahman 1953. "A neural network approach for the solution of Traveling Salesman and basic vehicle routing problems." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282498.
Full textAbstract:
Easy to explain and difficult to solve, the traveling salesman problem, TSP, is to find the minimum distance Hamiltonian circuit on a network of n cities. The problem cannot be solved in polynomial time, that is, the maximum number of computational steps needed to find the optimum solution grows with n faster than any power of n. Very good combinatoric solution approaches including heuristics with worst case lower bounds, exist. Neural network approaches for solving TSP have been proposed recently. In the elastic net approach, the algorithm begins from m nodes on a small circle centered on the centroid of the distribution of cities. Each node is represented by the coordinates of the related point in the plane. By successive recalculation of the position of nodes, the ring is gradually deformed, and finally it describes a tour around the cities. In another approach, the self organizing feature map, SOFM, which is based on Kohonen's idea of winner takes all, fewer than m nodes are updated at each iteration. In this dissertation I have integrated these two ideas to design a hybrid method with faster convergence to a good solution. On each iteration of the original elastic net method two nx m matrices of connection weights and inter node-city distances must be calculated. In our hybrid method this has been reduced to the calculation of one row and one column of each matrix, thus, If the computational complexity of the elastic net is O(n x m) then the complexity of the hybrid method is O(n+m). The hybrid method then is used to solve the basic vehicle routing problem, VRP, which is the problem of routing vehicles between customers so that the capacity of each vehicle is not violated. A two phase approach is used. In the first phase clusters of customers that satisfy the capacity constrain are formed by using a SOFM network, then in the second phase the above hybrid algorithm is used to solve the corresponding TSP. Our improved method is much faster than the elastic net method. Statistical comparison of the TSP tours shows no difference between the two methods. Our computational results for VRP indicate that our heuristic outperforms existing methods by producing a shorter total tour length.
26
Qiang, Qiang. "Network efficiency/performance measurement with vulnerability and robustness analysis with application to critical infrastructure." Amherst, Mass. : University of Massachusetts Amherst, 2009. http://scholarworks.umass.edu/dissertations/AAI3372272/.
Full text
27
Richmond, Nathaniel. "On stochastic network design: modeling approaches and solution techniques." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2264.
Full textAbstract:
Network design problems have been prevalent and popular in the operations research community for decades, because of their practical and theoretical significance. Due to the relentless progression of technology and the creative development of intelligent, efficient algorithms, today we are able to efficiently solve or give excellent heuristic solutions to many network design problem instances. The purpose of this work is to thoroughly examine and tackle two classes of highly complex network design problems which find themselves at the cutting edge of modern research.
First we examine the stochastic incremental network design problem. This problem differs from traditional network design problems through the addition of both temporal and stochastic elements. We present a modeling framework for this class of problems, conduct a thorough theoretical analysis of the solution structure, and give insights into solution methods.
Next we introduce the robust network design problem with decision-dependent uncertainties. Traditional stochastic optimization approaches shy away from randomness which is directly influenced by a user's decisions, due to the computational challenges that arise. We present a two-stage stochastic programming framework, noting that the complexity of this class of problems is derived from a highly nonlinear term in the first-stage objective function. This term is due to the decision-dependent nature of the uncertainty. We perform a rigorous computational study in which we implement various solution algorithms which are both exact and heuristic, as well as both well-studied and original.
For each of the two classes of problems examined in our work, we give suggestions for future study and offer insights into effective ways of tackling these problems in practice.
28
Wynter, Sharolyn Antonia. "Modeling to Quantify the Capacity and Efficacy of Emergency Preparedness and Response Systems: A Study of the North Carolina Health Alert Network." NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-05142009-010831/.
Full textAbstract:
Following the attacks of September 11th, the growing fear of a bioterrorist attack emerged within the United States and pushed the threat of bioterrorism to the forefront of the public health emergency preparedness and response agenda. Despite the investment of more than six billion dollars in federal funding towards emergency preparedness and response initiatives, well defined and broadly accepted performance measures for determining the efficacy of these systems have yet to be established. Because of the complex and dynamic conditions under which emergency preparedness and response systems must perform, it is becoming apparent that traditional measures of evaluating the performance of public health systems simply will not suffice. The inability to accurately capture and quantify this information has created knowledge gaps which hinder our ability to measure our true level of preparedness and ultimately weakens our response capacity. It is therefore essential that we develop methodologies that enable us to establish valid metrics which capture the information needed to quantify the capacity and efficacy of these systems. As a key information sharing and communication component of North Carolinaâs Public Health Information Network (NC PHIN), the North Carolina Health Alert Network (NCHAN) serves as a promising means to measure emergency preparedness and response capacity. The goal of this thesis is to present a methodology for extending approaches in operations research and systems engineering to better understand the value of emergency preparedness and response systems, such as NCHAN. Ultimately we seek to determine how NCHAN has aided to emergency preparedness and response by quantifying the added value of the system to the greater âpreparedness and responseâ process. We demonstrate the use of statistical analysis, simulation and the IDEF0 mapping process as valid tools for modeling and quantifying the less-tangible aspects of emergency preparedness and response. We find that although the capacity exists within NCHAN to increase emergency preparedness and response, other factors, such as usage variability amongst NCHAN users, lack of integration with other NC PHIN components, and limited capacity of tangible system resources (such as labs, funding and public health practitioners) limits the efficacy of NCHAN. These findings suggest that user standardization, component integration and proper resource allocation will be necessary in order to realize the true value of emergency preparedness and response systems.
29
Frumin, Michael S. "Automatic data for applied railway management : passenger demand, service quality measurement, and tactical planning on the London Overground Network." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61512.
Full textAbstract:
Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (p. 201-209).<br>The broad goal of this thesis is to demonstrate the potential positive impacts of applying automatic data to the management and tactical planning of a modern urban railway. Tactical planning is taken here to mean the set of transport-specific analysis and decisions required to manage and improve a railway with time horizons measured in weeks, months, or up to a year and little or no capital investment requirements. This thesis develops and tests methods to (i) estimate on-train loads from automatic measurements of train payload weight, (ii) estimate origin-destination matrices by combining multiple types of automatic data, (iii) study passenger incidence (station arrival) behavior relative to the published timetable, (iv) characterize service quality in terms of the difference between automatically measured passenger journey times and journey times implied by the published timetable. It does so using (i) disaggregate journey records from an entry- and exit-controlled automatic fare collection system, (ii) payload weight measurements from "loadweigh" sensors in train suspension systems, and (iii) aggregate passenger volumes from electronic station gatelines. The methods developed to analyze passenger incidence behavior and service quality using these data sources include new methodologies that facilitate such analysis under a wide variety of service conditions and passenger behaviors. The above methods and data are used to characterize passenger demand and service quality on the rapidly growing, largely circumferential London Overground network in London, England. A case study documents how a tactical planning intervention on the Overground network was influenced by the application of these methods, and evaluates the outcomes of this intervention. The proposed analytical methods are judged to be successful in that they estimate the desired quantities with sufficient accuracy and are found to make a positive contribution to the Overground's tactical planning process. It is concluded that relative measures of service quality such as the one developed here can be used in cross-sectional analysis to inform tactical planning activity. However, such measures are of less utility for longitudinal evaluation of tactical planning interventions when the basis against which service quality is judged (in this case the timetable) is changed. Under such circumstances, absolute measures, such as total observed passenger journey times, should be used as well.<br>by Michael S. Frumin.<br>S.M.<br>S.M.in Transportation
30
Nyamugure, Philimon. "Modification, development, application and computational experiments of some selected network, distribution and resource allocation models in operations research." Thesis, University of Limpopo, 2017. http://hdl.handle.net/10386/1930.
Full textAbstract:
Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2017<br>Operations Research (OR) is a scientific method for developing quantitatively
well-grounded recommendations for decision making. While it is true that it
uses a variety of mathematical techniques, OR has a much broader scope. It is
in fact a systematic approach to solving problems, which uses one or more analytical
tools in the process of analysis. Over the years, OR has evolved through
different stages. This study is motivated by new real-world challenges needed
for efficiency and innovation in line with the aims and objectives of OR – the
science of better, as classified by the OR Society of the United Kingdom. New
real-world challenges are encountered on a daily basis from problems arising
in the fields of water, energy, agriculture, mining, tourism, IT development,
natural phenomena, transport, climate change, economic and other societal requirements.
To counter all these challenges, new techniques ought to be developed.
The growth of global markets and the resulting increase in competition
have highlighted the need for OR techniques to be improved. These developments,
among other reasons, are an indication that new techniques are needed
to improve the day-to-day running of organisations, regardless of size, type and
location.
The principal aim of this study is to modify and develop new OR techniques
that can be used to solve emerging problems encountered in the areas of linear
programming, integer programming, mixed integer programming, network
routing and travelling salesman problems. Distribution models, resource allocation
models, travelling salesman problem, general linear mixed integer
ii
programming and other network problems that occur in real life, have been
modelled mathematically in this thesis. Most of these models belong to the
NP-hard (non-deterministic polynomial) class of difficult problems. In other
words, these types of problems cannot be solved in polynomial time (P). No general
purpose algorithm for these problems is known. The thesis is divided into
two major areas namely: (1) network models and (2) resource allocation and
distribution models. Under network models, five new techniques have been developed:
the minimum weight algorithm for a non-directed network, maximum
reliability route in both non-directed and directed acyclic network, minimum
spanning tree with index less than two, routing through 0k0 specified nodes,
and a new heuristic to the travelling salesman problem. Under the resource
allocation and distribution models section, four new models have been developed,
and these are: a unified approach to solve transportation and assignment
problems, a transportation branch and bound algorithm for the generalised assignment
problem, a new hybrid search method over the extreme points for
solving a large-scale LP model with non-negative coefficients, and a heuristic
for a mixed integer program using the characteristic equation approach. In
most of the nine approaches developed in the thesis, efforts were done to compare
the effectiveness of the new approaches to existing techniques. Improvements
in the new techniques in solving problems were noted. However, it was
difficult to compare some of the new techniques to the existing ones because
computational packages of the new techniques need to be developed first. This
aspect will be subject matter of future research on developing these techniques
further. It was concluded with strong evidence, that development of new OR
techniques is a must if we are to encounter the emerging problems faced by the
world today.
Key words: NP-hard problem, Network models, Reliability, Heuristic, Largescale
LP, Characteristic equation, Algorithm.
31
Seyhan, Tolga Han. "An Intertemporal And Spatial Network Model For Turkish Energy System." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608594/index.pdf.
Full textAbstract:
Turkey, as a recent signatory to the United Nations Framework Convention on Climate Change (UNFCCC) has to adopt policies to restrict greenhouse gas emissions at a time when energy demand is increasing rapidly. We report on an intertemporal, spatial network model representing the energy system that seeks to address the difficult trade-offs involved. We compute and optimal mix of fuels and technologies<br>considering efficiencies and investments in generation and transmission. The model allows analysis of emissions and investment decisions to attain set targets. Extensions allowing the study of dependency on fossil fuels and imports are also discussed.
32
Li, Shuting. "Linking Contextual Drivers, Network Responses, Risk Management Capabilities, and Sustainable Outcome: Theoretical Framework and Empirical Examination." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1467035463.
Full text
33
Wang, Shuo. "Optimization Models for Network-Level Transportation Asset Preservation Strategies." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1416578565.
Full text
34
Pfeiffer, Volker. "Communication aspects in urban terrain." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FPfeiffer.pdf.
Full textAbstract:
Thesis (M.S. in Operations Research)--Naval Postgraduate School, December 2006.<br>Thesis Advisor(s): Tom Lucas. "December 2006." Includes bibliographical references (p. 73-74). Also available in print.
35
Jiang, Tianyu. "Data-Driven Cyber Vulnerability Maintenance of Network Vulnerabilities with Markov Decision Processes." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494203777781845.
Full text
36
Armstrong, Austin James. "Electronic Poll Book Allocation in Ohio." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1594851013751813.
Full text
37
Wu, Fei. "Electric Vehicle Charging Network Design and Control Strategies." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1479900508609434.
Full text
38
Gao, Meihui. "Models and Methods for Network Function Virtualization (NFV) Architectures." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0025/document.
Full textAbstract:
Avec la croissance exponentielle des demandes de service, les opérateurs ont déployé de nombreux équipements, et par conséquent, la gestion du réseau est devenue de plus en plus difficile et coûteuse. La virtualisation des fonctions réseau (NFV) a été proposée comme un nouveau paradigme pour réduire les coûts liés à l’acquisition et à la maintenance pour les réseaux de télécommunications. Dans ce travail de thèse, nous nous intéressons aux problèmes du chaînage des fonctions virtuelles (VNFs) qui combinent des décisions de localisation des VNFs et de routage des demandes. D'un point de vue d'optimisation, ce problème est une combinaison des problèmes de localisation (pour la partie d'installation des VNFs) et de conception de réseaux (pour la partie de routage). Ces deux problèmes ont été largement étudié dans la littérature. Cependant, leur combinaison représente des divers challenges en termes de modélisation et de résolution. Dans la première partie de cette thèse, nous considérons une version réaliste du problème du chaînage des VNFs (VNF-PR) afin de comprendre l'impact des différents aspects sur les coûts et les performances de gestion du réseau. Dans ce but, nous étendons le travail dans~\cite{Addis2015} en considérant des caractéristiques et des contraintes plus réalistes des infrastructures NFV et nous proposons un modèle de programmation linéaire et une heuristique mathématique pour le résoudre. Dans le but de mieux comprendre la structure du problème et ses propriétés, la deuxième partie de la thèse est orientée vers l'étude théorique du problème, où nous avons étudié une version compacte du problème du chaînage des VNFs. Nous fournissons des résultats sur la complexité de calcul sous divers cas de topologie et de capacité. Ensuite, nous proposons deux modèles et nous les testons sur un testbed avec plus de 100 instances différentes avec différents cas de capacité. Au final, nous abordons la scalabilité du problème en proposant des méthodes constructives et des méthodes heuristiques basées sur la programmation linéaire entière pour traiter efficacement des instances de taille grande (jusqu'à 60 nœuds et 1800 demandes). Nous montrons que les heuristiques proposées sont capables de résoudre efficacement des instances de taille moyenne (avec jusqu'à 30 nœuds et 1 000 demandes) de cas de capacité difficiles et de trouver de bonnes solutions pour les instances dures, où le modèle ne peut fournir aucune solution avec un temps de calcul limité<br>Due to the exponential growth of service demands, telecommunication networks are populated with a large and increasing variety of proprietary hardware appliances, and this leads to an increase in the cost and the complexity of the network management. To overcome this issue, the NFV paradigm is proposed, which allows dynamically allocating the Virtual Network Functions (VNFs) and therefore obtaining flexible network services provision, thus reducing the capital and operating costs. In this thesis, we focus on the VNF Placement and Routing (VNF-PR) problem, which aims to find the location of the VNFs to allocate optimally resources to serve the demands. From an optimization point of view, the problem can be modeled as the combination of a facility location problem (for the VNF location and server dimensioning) and a network design problem (for the demands routing). Both problems are widely studied in the literature, but their combination represents, to the best of our knowledge, a new challenge. We start working on a realistic VNF-PR problem to understand the impact of different policies on the overall network management cost and performance. To this end, we extend the work in [1] by considering more realistic features and constraints of NFV infrastructures and we propose a linear programming model and a math-heuristic to solve it. In order to better understand the problem structure and its properties, in the second part of our work, we focus on the theoretical study of the problem by extracting a simplified, yet significant variant. We provide results on the computational complexity under different graph topology and capacity cases. Then, we propose two mathematical programming formulations and we test them on a common testbed with more than 100 different test instances under different capacity settings. Finally, we address the scalability issue by proposing ILP-based constructive methods and heuristics to efficiently deal with large size instances (with up to 60 nodes and 1800 demands). We show that our proposed heuristics can efficiently solve medium size instances (with up to 30 nodes and 1000 demands) of challenging capacity cases and provide feasible solutions for large size instances of the most difficult capacity cases, for which the models cannot find any solution even with a significant computational time
39
Kroener, Martina Ursula. "Multi-level Analytic Network Process Model to Mitigate Supply Chain Disruptions in Disaster Recovery Planning." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1540.
Full textAbstract:
Over the past few decades, environmental changes have led to more frequent occurrences and greater intensities of natural disasters worldwide. In terms of globally connected supply chains, this has resulted in an enormous economical loss for corporations. Therefore, Business Continuity and Disaster Recovery (BC/DR) planning and management has become essential for businesses in order to protect their critical business flow. Yet there is a lack of systematic and transparent methodologies for companies to handle this problem.
Hence, this thesis introduces a novel approach to combine consecutive steps of the Disaster Recovery Planning (DRP) process within one application. The multi-criteria decision-making (MCDM) tool called the Analytic Network Process (ANP) is employed to identify critical products of a business and match them with optimal disruption mitigation strategies based on an evaluation of benefits, opportunities, costs, and risks (BOCR).
To validate the method developed in this thesis, a case study using historical data of a U.S. company (Company XYZ) is introduced. The results of the ANP mathematical modeling demonstrate that the developed methodology provides a valuable approach to analyze and confirm BC/DR planning decisions. Moreover, an expert of Company XYZ confirmed that the suggested solution established through this case study is in agreement with the preferable choice based on his expertise and professional decision-making.
Further research could extend the proposed methodology to other fields of BC/DR planning, such as IT Disaster Recovery Planning or Human Disaster Relief.
40
Taylor, Daniel. "Channel Fulfillment Characteristics, Retail Network Structure and Buy-Online-Ship-From-Store Performance: Inventory Behavior and Channel Service Implications." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531426717885577.
Full text
41
Groves, G. W. "Scheduling evenly spaced routes in networks." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/16055.
Full text
42
Erenay, Bulent. "Concurrent Supply Chain Network & Manufacturing Systems Design Under Uncertain Parameters." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1459206318.
Full text
43
George, David K. "Stochastic Modeling and Decentralized Control Policies for Large-Scale Vehicle Sharing Systems via Closed Queueing Networks." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338387102.
Full text
44
Eskandarpour, Majid. "Generic models and optimization algorithms for sustainable supply chain network design." Thesis, Nantes, Ecole des Mines, 2014. http://www.theses.fr/2014EMNA0195/document.
Full textAbstract:
Cette thèse porte sur le développement de modèles mathématiques et d’algorithmes d’optimisation pour la conception de chaînes logistiques durables. Nous proposons des modèles mono-périodiques, multi-produits et multi-modes de transport à quatre niveaux (fournisseurs, unités de production, entrepôts et clients) couvrant les piliers économique et environnemental du développement durable. Les variables de décision concernent la localisation des sites logistiques intermédiaires (unités de production et entrepôts), les choix de technologie et de mode de transport, et la détermination des flux de produits. Un premier modèle est basé uniquement sur la minimisation des coûts totaux. Ce modèle est étendu au cas bi-objectif en considérant la minimisation des émissions de CO2. Nous proposons une procédure d’optimisation basée sur la recherche à voisinage large (LNS : Large Neighborhood Search). L’application de cette méthode à un problème à variables mixtes tel que la conception de chaîne logistique est inédite. Notre extension au cas bi-objectif fait intervenir l’algorithme récent de recherche locale multi-directionnelle. Les expérimentations numériques permettent d’évaluer la pertinence de nos modèles et de comparer les performances de nos algorithmes à celles d’un solveur du marché<br>This thesis focuses on the development of mathematical models and optimization algorithms for the design of sustainable supply chains. We propose single-period, multi-commodity, multi-mode, four level models (suppliers, production facilities, warehouses and customers) covering economic and environmental pillars of sustainable development. The decision variables are related to the location of the intermediate logistics sites (production units and warehouses), the choice of technology and mode of transport, and the determination of product flow. A first model is based solely on minimizing total costs. This model is extended to bi-objective minimization by considering CO2 emissions. We propose an optimization procedure based on the Large Neighborhood Search (LNS) metaheuristic, which had almost never been applied to problems with mixed variables such as design supply chain. Our extension to the bi-objective case involves the use of the multi-directional local search (MDLS). Extensive numerical experiments assess the relevance of our model and compare the performance of our algorithms to those of a state-of-the-art solver
45
Farias, Everton da Silveira. "A heuristic approach to supply chain network design in a multi-commodity four-echelon logistics system." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/140332.
Full textAbstract:
Nesta tese propõe-se um método heurístico para o problema de Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) considerando vários aspectos de relevância prática, tais como: fornecedores e matérias-primas, localização e operação de instalações, atribuição de Centros de Distribuição (CD), e grande número de clientes e produtos. Uma eficiente abordagem heurística de duas fases é proposta para a obtenção de soluções viáveis para os problemas, que inicialmente é modelado como um Programa Linear Inteiro Misto (PLIM) de grande escala. Na fase de construção, uma estratégia de Linear Programming Rounding é aplicada para se obter os valores iniciais para as variáveis de localização inteira do modelo. Simultaneamente, um método Multi-start foi desenvolvido para gerar soluções iniciais diversificadas para cada nova iteração da heurística de Rounding. Na segunda fase, dois procedimentos de Busca Local foram desenvolvidos no sentido de melhorar a solução fornecida pelo método de Rounding. Implementamos duas diferentes abordagens de Busca Local: remoção-inserção e troca. Uma técnica de Busca Tabu para orientar o procedimento de Busca Local para explorar os diferentes espaços de soluções foi desenvolvida. As formulações e algoritmos foram implementados na linguagem C++ utilizando ferramentas de otimização da COIN-OR. O método de solução foi experimentado em instâncias geradas aleatoriamente, com tamanhos diferentes em termos do número de parâmetros, tais como o número de produtos, zonas de clientes, CDs e fábricas considerando um sistema logístico de quatro níveis. As implementações computacionais mostram que o método de solução proposto obteve resultados satisfatórios quando comparados com a literatura. Para validar este método heurístico também foi usado em um caso realista, com base em dados de uma empresa de borracha que está reestruturando sua cadeia de suprimentos devido ao projeto de uma nova uma nova fábrica e produção de novos produtos. A abordagem heurística proposta revelou-se adequada para aplicação prática em um caso real de uma indústria multicommodity em um contexto determinístico.<br>In this thesis we propose a heuristic method for the Supply Chain Network Design (SCND) problem considering several aspects of practical relevance: suppliers and raw materials, location and operation facilities, distribution center (DC) assignments, and large numbers of customers and products. An efficient two-phase heuristic approach is proposed for obtaining feasible solutions to the problems, which is initially modeled as a large-scale Mixed Integer Linear Program (MILP). In the construction phase, a linear programming rounding strategy is applied to obtain initial values for the integer location variables in the model. Simultaneously, a Multi-start method was developed to generate diversified initial solutions from each new iteration in the rounding heuristic. In the second phase, two Local Search procedures were developed towards to improve the solution provided by the rounding method. We implemented two different Local Search approaches: removal-insertion and exchange. A Tabu Search technique was developed to guide the Local Search procedure to explore the different spaces of solutions. The formulations and algorithms were implemented in C++ code language using the optimization engine COIN-OR. The solution method was experimented in randomly generated instances, with different sizes in terms of the number of parameters, such as number of products, customer zones, DCs, and factories considering a four-echelon logistic system. The computational implementations show that the solution method proposed obtained satisfactory results when compared to the literature review. To validate this heuristic method was also used in a realistic case, based on data from a rubber company that is restructuring its supply chain due to the overture of a new factory, producing new products. The proposed heuristic approach proved appropriate to practical application in a realistic case of a multi commodity industry in a deterministic context.
46
Maragno, Donato. "Optimization with machine learning-based modeling: an application to humanitarian food aid." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21621/.
Full textAbstract:
In this thesis, we propose a machine learning-based optimization methodology to build (part of) optimization models with a data-driven approach. This approach is useful whenever we have to model one or more relations between the decisions and their impact on the system. This kind of relationship can be challenging to model manually, and so machine learning is used to learn it through the use of data.
We demonstrate the potential of this method through a case study in which a predictive model is used to approximate the palatability scoring function in a typical diet problem formulation. First, the performance of this approach is analyzed by embedding a Linear Regression model and then by embedding a Fully Connected Neural Network.
47
Taslim, Cenny. "Multi-Stage Experimental Planning and Analysis for Forward-Inverse Regression Applied to Genetic Network Modeling." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1213286112.
Full text
48
Trapote, Barreira César. "Methodology for optimal design of efficient air transport network in a competitive environment." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/350317.
Full textAbstract:
This thesis aims to dissert about air transport network design taking into consideration the current needs about efficiency in a very competitive industry. The main focus for this work is the airline's point of view and for this reason is going to be common to talk about profitability.
A methodology is proposed to analyse current networks and to introduce modifications. First, an analytical approach is proposed with the aim to understand better the interaction of key parameters in network design at strategical level. Analyitical models demonstrate to be very useful because with a few parameters it is possible to decide if point to point or hub and spoke configuration suits better for an airline, given a set of supply conditions. Furthermore, the performance of networks with stopover configuration is tested, basically because for long routes with low demand this newtorks work well, how it was demonstrated by public transport systems. The differenciation of this research, compared against previous studies, is to include the performance of new entrant airlines in the industry. This aspect is carried out evaluating accurately the impact of fixed costs in the evaluation of cost operators. Despite airlines tend to consider aircraft ownership costs and labor costs as variable ones, they are not. They had an important impact in profit and loss account. A bad utilitzation factor of airplane or crew staff is very undesirable for operator and it can consider do not operate new routes if the resources are not well used.
Secondly, analytical models are powerful but it is not possible to evaluate accurately the daily operational aspects for real networks with real flight schedules because these models take into consideration average values of some parameters. For this reason, this thesis develops a Tabu search algorithm to carry out airline network planning, based on linear models of each different planning problem. To do this contribution, these models are developed before for linear programming and they are solved with a combination of complete enumeration algorithm and exhaustive search algorithm. Both algorithms provide exact solution or global optimum for any problem statement. Later, Tabu search algorithm improves performance of searching with lower computational cost. The main conclusion is that Tabu developed is a better tool for airline planning than exact techniques because of lower times of computation. This performs better for large networks that, finally, are real networks. However, exact techniques could be interesting for small airlines that can be start-ups.
Third, one of main reasons to develop a quantification of costs for managing airlines is due to the problem of complexity in networks. With the growth of air transportation and congestion at airports, primary or reactionary delays become higher day after day. Reactiveness of network depends of configuration and planning. Airlines manages it with extra reources, one way is allocating buffer times in flight schedule and other is having aircrafts at ground at main bases to enter in service and recover flight plans. Airline network design, planning and efficient algorithms are key assets to provide robustness for airlines.
Finally, driving airlines in high competitive environments are difficult. Running low costs is the main decision for managers. However, analysing the problem from theory game point of view, allows finding key reasons to support this argument. First, a Stakelberg model is defined for two competing airlines. This model demonstrates that a war on frequencies or fares damages both competitors. Furthermore, a Cournot model it is shown and it proposes a navigation fee attending to correct utilization of capacity. Both models are a theoretical framework but demonstrate consistency and encourage further investigations.<br>El diseño de redes de transporte aéreo es un factor clave de eficiencia en una industria altamente competitiva. A pesar de que la rentabilidad es de suma importancia, el sistema considera la experiencia del usuario y los beneficios sociales para obtener un óptimo global. Un enfoque analítico permite derivar principios de diseño de redes de transporte aéreo: la tesis muestra cómo unas pocas variables y sus interacciones explican los factores clave del diseño de la red a nivel estratégico. Los servicios punto-a-punto muestran supremacía en las redes simples y para demandas altas y compensadas, una configuración con escalas es adecuada para rutas lejanas con poca demanda, y las operaciones hub and spoke mejoran las dos estrategias anteriores para redes grandes, cuando la demanda es baja o cuando las frecuencias son altas, pero son más
sensibles a la propagación de demoras.
El enfoque analítico permite prever el comportamiento de nuevas compañías aéreas entrando en el sector. El modelo incluye costes fijos de propiedad del avión y laborales (al contrario de las hipótesis habituales de la industria, que trabaja con costes variables), puesto que tienen un impacto importante en la cuenta de resultados.
Una vez se han derivado guías de diseño, la tesis formula un planteamiento más realista del diseño de redes de transporte aéreo basado en programación matemática lineal, que se resuelve con una combinación del Algoritmo de Enumeración Completa y el Algoritmo de Búsqueda Exhaustiva (ambos proporcionan la solución exacta o un óptimo global para cualquier planteamiento del problema). El modelo incluye asignación de flotas, rutas de aeronaves y programación de tripulaciones. Mientras que los algoritmos exactos son apropiados para aerolíneas pequeñas, los
problemas más grandes necesitan Búsqueda Tabú.
El crecimiento del transporte aéreo y la congestión en los aeropuertos (a veces propiciada por las operaciones hub&spoke) pueden afectar las demoras con un efecto de bola de nieve o látigo; sin embargo el análisis de la complejidad de la red aérea puede incrementar la resiliencia de las
operaciones. Un buen diseño de la red aérea, una buena planificación y unos algoritmos eficientes, son aspectos clave para proporcionar fiabilidad a las aerolíneas y así reducir los recursos inactivos asociados a “colchones de tiempo” (en los horarios de los vuelos) y/o en aviones “de reserva” en la plataforma para recuperar planes de vuelo. El “acolchado” mejora la percepción de la calidad por parte del pasajero, pero con un control activo del horario de vuelos puede conseguirse la misma percepción con costes menores.
El entorno competitivo de las aerolíneas se analiza con teoría de juegos: un modelo de Stakelberg para dos aerolíneas competidoras muestra que una guerra de frecuencias o tarifas es perjudicial para ambas aerolíneas. Un modelo Cournot propone una tasa de navegación y de congestión según la correcta utilización de la capacidad. Vuelos (de la misma alianza) a lo largo del mundo con escalas en los hubs principales se proponen como investigación futura
49
Huang, Jing. "Resource Management and Sourcing Strategies in Supply Chain Coordination under an Uncertain Environment." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1354756891.
Full text
50
Hulett, Maria. "Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing." FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/167.
Full textAbstract:
Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.