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Mobasherfar, Mir Kamran. "Disturbance management for shop floor scheduling." Thesis, Cranfield University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359944.
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Herrmann, Jan. "Supply chain scheduling." Wiesbaden Gabler, 2009. http://d-nb.info/999948970/04.
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Khamooshi, H. "Heuristic network-based project scheduling : dynamic priority scheduling method; DPSM." Thesis, Lancaster University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267918.
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Carney, Donald P. "Application-aware resource scheduling /." View online version; access limited to Brown University users, 2005. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3174582.
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Mu, Qianxin. "Disruption management in vehicle routing and scheduling." Thesis, Lancaster University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543984.
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Cancian, Glen Andrew. "Heuristic Based Optimisation of Pavement Management Scheduling." Thesis, Griffith University, 2016. http://hdl.handle.net/10072/366768.
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The issue of effectively scheduling pavement maintenance and rehabilitation treatments over a multi-year planning horizon plagues road authorities around the world with the significance of this issue being amplified by both an ageing pavement network and the trend towards insufficient fund allocation. The scope of the problem can be quantified as follows: if only a single treatment is able to be applied to each individual road segment in a single year, then the total number of possible programmed maintenance and rehabilitation schedule alternatives for a moderate-sized network of 1,000 road segments, with eight different treatments possible, over a twenty year anaysis period is ((1.0 × 103)8)20 = 1.0 × 10480. Assuming that a computer can build and evaluate 100 complete maintenance and rehabilitation schedules a second, to identify the optimal schedule for this 1,000 segment road network would take 3.17 × 10471 years. The overall goal of this study is to investigate the benefits of applying modern heuristic optimisation techniques to the problem of pavement main- tenance and rehabilitation scheduling over a multi-year planning horizon. To address this goal, a four stage approach was utilised using a real road network with real pavement condition data as the test benchmark.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>Griffith School of Engineering<br>Science, Environment, Engineering and Technology<br>Full Text
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Gould, Rebecca (Rebecca L. ). "Program scheduling : decreasing flow by back-scheduling." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104396.
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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.<br>Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 74).<br>The Boeing 737 program has announced that they will continue to increase their production rate from 42 airplanes per month to eventually 52 airplanes per month. In order for the field to accommodate the increased production rates, opportunities are being considered for decreasing airplane production flow and the increasing capacity in the field. This thesis focuses on the opportunity for decreasing schedule flow through improvements in the scheduling process. Currently the field constraints do not heavily influence what order the planes roll out of the factory. This causes the field to deal with constraint variation by addressing the airplane schedule flow in order to make delivery. This thesis contributes to focusing on improving the scheduling process by driving more information being shared upstream in the decision making process and therefore decreasing the number of days needed to prepare the airplane for delivery.<br>by Rebecca Gould.<br>M.B.A.<br>S.M. in Engineering Systems
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Ou, Jihong. "Dynamic scheduling of queueing networks." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13479.
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Kassab, Hisham Ibrahim. "Scheduling in packet radio networks." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9927.
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Charrier, Ghislain. "Scheduling and Dynamic Management of Applications over Grids." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2010. http://tel.archives-ouvertes.fr/tel-00590292.
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Les travaux présentés dans cette thèse portent sur l'ordonnancement d'applications au sein d'un environnement de grille de calcul. Nous étudions comment mieux gérer les tâches au sein des intergiciels de grille, ceci dans l'objectif d'améliorer les performances globales de la plateforme. Les solutions que nous proposons se situent dans l'intergiciel, ce qui permet de conserver les architectures sous-jacentes sans les modifier. Dans un premier temps, nous proposons un mécanisme de réallocation permettant de prendre en compte dynamiquement les erreurs d'ordonnancement commises lors de la soumission de calculs. En effet, lors de la soumission sur une machine parallèle, il est souvent nécessaire de fournir une estimation du temps d'exécution afin que celle-ci puisse effectuer un ordonnancement. Cependant, les estimations ne sont pas précises et les décisions d'ordonnancement sont sans cesse remises en question. Le mécanisme de réallocation proposé permet de prendre en compte ces changements en déplaçant des calculs d'une machine parallèle à une autre. Le second point auquel nous nous intéressons dans cette thèse est l'ordonnancement d'une application de climatologie sur la grille. Afin de fournir les meilleures performances possibles nous avons modélisé l'application puis proposé des heuristiques spécifiques. Pour exécuter l'application sur une grille de calcul, l'intergiciel utilise ces connaissances sur l'application pour fournir le meilleur ordonnancement possible.
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Tanwir, Savera. "Network Resource Scheduling and Management of Optical Grids." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-05082007-194445/.
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Advance reservation of lightpaths in an optical network has become a popular concept of reserving network resources in support of Grid applications. In this thesis, we have evaluated and compared several algorithms for dynamic scheduling of lightpaths using a flexible advance reservation model. The main aim is to find the best scheduling policy that improves network utilization and minimizes blocking. The scheduling of lightpaths involve both routing and wavelength assignment. Our simulation results show that minimum cost adaptive routing where link costs are determined by the current and future usage of the link provides the minimum blocking. Moreover, searching for k alternate paths within the scheduling window significantly improves the performance. For wavelength assignment, we have used a scheme that reduces fragmentation by minimizing unused leading or trailing gaps. We have also analyzed approaches for failure recovery and lightpath re-optimization. Finally, an advance reservation scheme needs timely information regarding the status of the optical links. To this end, we have surveyed various monitoring tools and techniques and we have proposed a monitoring framework to support fast restoration.
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Reinhard, Erik. "Scheduling and data management for parallel ray tracing." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302169.
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Whitehead, Jonathan David. "Scheduling and layout in flexible manufacturing systems." Thesis, University of Southampton, 2002. https://eprints.soton.ac.uk/50617/.
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This thesis covers a variety of inter-related scheduling and layout issues encountered in flexible manufacturing systems. The principal focus is upon systems which adopt the commonly implemented loop layout configuration. A pivotal idea behind the work is that products must revisit machines during their manufacture. The work encompasses both computational and theoretical results. The computational work consists of testing both new and standard heuristic and local search techniques on two strongly NP-hard combinatorial optimisation problems, one related to layout and the other to single machine scheduling. In the layout problem, machines must be sequenced around a loop of conveyor belt with the objective of minimising the amount of movement carried out by the worst affected product type within the manufacturing system. In the single machine scheduling problem, coupledoperation jobs must be scheduled so that the maximum completion time on the machine, the makespan, is minimised; each coupled-operation job consists of two arbitrary processing time operations separated by a time lag that is bounded both below and above. Our results suggest that local search techniques, while well suited to standard search spaces, do not perform well when the search space contains infeasible neighbours and the cost of evaluating candidate solutions is high. The theoretical work stems from the repetitive manufacture of single product types in loop layout flexible manufacturing systems. We demonstrate that in such a system, the efficiency is strongly governed by the balance of workloads on the machines. We develop mixed integer programming models for tool allocation and machine sequencing with the objective of balancing workloads, and as a secondary criterion, minimising product movement. Focusing on a single machine, we study the computational complexity of a class of coupled-operation scheduling problems; each job consists of two unit processing time operations separated by a fixed delay of two units of time, and their order of production is restricted by precedence constraints. For several standard scheduling objective functions, we provide either polynomial algorithms or proof of NP-hardness for parallel chain and tree precedence constraints.
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Deshpande, Sawan P. (Sawan Prashant) 1975. "A scheduling policy experiment for lean implementation." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/82678.
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Thesis (S.M.M.O.T.)--Massachusetts Institute of Technology, Sloan School of Management, Management of Technology Program, 1999.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (leaves 178-184).<br>by Sawan P. Deshpande.<br>S.M.M.O.T.
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Miller, Jeremy John. "Production scheduling in a foundry machine shop." Master's thesis, University of Cape Town, 1986. http://hdl.handle.net/11427/21924.
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Bibliography: pages 89-92.<br>The scheduling of production in job shops is generally accomplished in four stages; aggregate planning, machine loading, sequencing and detailed scheduling. In industrial job shops, the number of jobs and machines makes detailed scheduling a particularly complicated and unwieldy task. When faced with this situation, a typical response of managements is to simply ignore the problem and apply some remedial action by adapting existing company operation procedures. The first objective of this dissertation is to indicate the dangers and inefficiencies which result when the problem of detailed scheduling is ignored. This is done in terms of a case study analysis in which the problems which currently exist in the machine shop at Atlantis Aluminium, a jobbing foundry, are illustrated. The second objective is to develop a systematic approach for the solution of detailed scheduling in job shops. Major steps in this approach are: i) a classification of shop scheduling problems ii) a survey of relevant scheduling literature in order to determine existing detailed scheduling techniques iii) the design of the scheduling system This approach is illustrated by applying it to the machine shop at Atlantis Aluminium.
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Moon, Jeongseung. "Timing control in manufacturing and supply chains." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04072004-180111/unrestricted/moon%5Fjeongseung%5F200312%5Fphd.pdf.
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Moser, Huey D. "Scheduling and routing Tactical Aerial Reconnaissance Vehicles." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA239523.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990.<br>Thesis Advisor(s): Rosenthal, Richard E. Second Reader: Bloch, Paul S. "September 1990." Description based on title screen as viewed on March 19, 2010. DTIC Identifier(s): Unmanned Aaerial Vehicles. Author(s) subject terms: Heuristic Programming, Traveling Salesman Problem, Routing with time windows, Unmanned Aerial Vehicle. Includes bibliographical references (p. 56-57). Also available in print.
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Blanco-Freja, Edgar Emilio. "Coordinated production and distribution scheduling in supply chain management." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/25624.
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Svärd, Petter. "Dynamic Cloud Resource Management : Scheduling, Migration and Server Disaggregation." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-87904.
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A key aspect of cloud computing is the promise of infinite, scalable resources, and that cloud services should scale up and down on demand. This thesis investigates methods for dynamic resource allocation and management of services in cloud datacenters, introducing new approaches as well as improvements to established technologies.Virtualization is a key technology for cloud computing as it allows several operating system instances to run on the same Physical Machine, PM, and cloud services normally consists of a number of Virtual Machines, VMs, that are hosted on PMs. In this thesis, a novel virtualization approach is presented. Instead of running each PM isolated, resources from multiple PMs in the datacenter are disaggregated and exposed to the VMs as pools of CPU, I/O and memory resources. VMs are provisioned by using the right amount of resources from each pool, thereby enabling both larger VMs than any single PM can host as well as VMs with tailor-made specifications for their application. Another important aspect of virtualization is live migration of VMs, which is the concept moving VMs between PMs without interruption in service. Live migration allows for better PM utilization and is also useful for administrative purposes. In the thesis, two improvements to the standard live migration algorithm are presented, delta compression and page transfer reordering. The improvements can reduce migration downtime, i.e., the time that the VM is unavailable, as well as the total migration time. Postcopy migration, where the VM is resumed on the destination before the memory content is transferred is also studied. Both userspace and in-kernel postcopy algorithms are evaluated in an in-depth study of live migration principles and performance.Efficient mapping of VMs onto PMs is a key problem for cloud providers as PM utilization directly impacts revenue. When services are accepted into a datacenter, a decision is made on which PM should host the service VMs. This thesis presents a general approach for service scheduling that allows for the same scheduling software to be used across multiple cloud architectures. A number of scheduling algorithms to optimize objectives like revenue or utilization are also studied. Finally, an approach for continuous datacenter consolidation is presented. As VM workloads fluctuate and server availability varies any initial mapping is bound to become suboptimal over time. The continuous datacenter consolidation approach adjusts this VM-to-PM mapping during operation based on combinations of management actions, like suspending/resuming PMs, live migrating VMs, and suspending/resuming VMs. Proof-of-concept software and a set of algorithms that allows cloud providers to continuously optimize their server resources are presented in the thesis.
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Ait-Ali, Abderrahman. "Integration of Production Scheduling and Energy Management : Software Development." Thesis, KTH, Optimeringslära och systemteori, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-160136.
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Demand-Side Management concepts have the potential to positively impact the financial as well as the environmental aspects of energy-intensive industries. More specifically, they allow reducing the energy cost for the industrial plants by dealing with energy-availability fluctuations. In this context, efficient frameworks for scheduling with energy awareness have been studied and showed potential to reduce the overall energy bill for energy-intensive industries, for instance stainless steel and paper plants. Those frameworks usually combine scheduling and energy optimization into one monolithic system. This work investigates the possibility of integrating the two systems by specific exchange of signals, while keeping the scheduling model separated from the energy-cost optimization model. Such integration means that the pre-existent schedulers and energy optimizers could be easily modified and reused without re-implementing the whole new system. Two industrial problems with different scheduling approaches are studied. The first problem is about pulp and paper production which uses the Resource Task Network (RTN) scheduling approach. The second one is about stainless steel production which is based on a bi-level heuristic implementation of an improved energy-aware scheduler. This work presents the decomposition methods that are available in literature and their application to the two industrial problems. Besides an improvement in the RTN approach for handling storages, this thesis describes a prototype implementation of the energy-aware RTN scheduler for paper and pulp production. Furthermore, this work investigates the performance of the application of different decomposition methods on different problem instances. The numerical case studies show that even though the decomposition decreases the solution quality compared to the monolithic system, it still gives good solutions within an acceptable duration with the advantage of having two separate pre-existent systems which are simply exchanging signals.
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Brodard, Zacharie. "Workflow management and scheduling in a cloud computing context." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249714.
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Public cloud providers have had a tremendous impact on the software engineering world recently by offering on-demand computing infrastructures and scalable managed solutions. The goal of this master degree project is to determine whether these services offered by public cloud providers can improve the design of workflow management and scheduling systems for data-driven workflows. A cloud based architecture for a distributed workflow management system was designed, implemented and experimented on. It allowed to confirm the value of cloud computing solutions to solve workflow scheduling problems, by allowing to efficiently launch workloads on elastic computing resources.<br>På senaste tiden har public cloud-leverantörer haft stor effekt på mjukvaruingenjörsvetenskapen genom att föreslå databehandlingsinfrastrukturer på begäran samt skalbara lösningar. Målet med detta examensarbete är att fastställa om dessa tjänster, som föreslås av public cloud-leverantörer, kan förbättra designen av arbetsflödeshantering och schemaläggningssystem för datastyrda arbetsflöden. En molnbaserad arkitektur för ett distribuerat system av arbetsflödeshantering utformades, implementerades och testades. Genom effektivt utnyttjande av elastiska datorresurser kunde värdet av molnlösningar för att lösa schemaläggningsproblem i arbetsflöden bekräftas.
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Waldspurger, Carl A. "Lottery and stride scheduling : flexible proportional-share resource management." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36071.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (p. 145-151).<br>by Carl A. Waldspurger.<br>Ph.D.
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Austin, Amy Beth. "Management and scheduling aspects of increasing flexibility in manufacturing." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/37503.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1993, and Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1993 .<br>Includes bibliographical references (p. 167-169).<br>by Amy B. Austin.<br>M.S.
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Sedaghat, Mina. "Cluster Scheduling and Management for Large-Scale Compute Clouds." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112467.
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Cloud computing has become a powerful enabler for many IT services and new technolo-gies. It provides access to an unprecedented amount of resources in a fine-grained andon-demand manner. To deliver such a service, cloud providers should be able to efficientlyand reliably manage their available resources. This becomes a challenge for the manage-ment system as it should handle a large number of heterogeneous resources under diverseworkloads with fluctuations. In addition, it should also satisfy multiple operational require-ments and management objectives in large scale data centers.Autonomic computing techniques can be used to tackle cloud resource managementproblems. An autonomic system comprises of a number of autonomic elements, which arecapable of automatically organizing and managing themselves rather than being managedby external controllers. Therefore, they are well suited for decentralized control, as theydo not rely on a centrally managed state. A decentralized autonomic system benefits fromparallelization of control, faster decisions and better scalability. They are also more reliableas a failure of one will not affect the operation of the others, while there is also a lower riskof having faulty behaviors on all the elements, all at once. All these features are essentialrequirements of an effective cloud resource management.This thesis investigates algorithms, models, and techniques to autonomously managejobs, services, and virtual resources in a cloud data center. We introduce a decentralizedresource management framework, that automates resource allocation optimization and ser-vice consolidation, reliably schedules jobs considering probabilistic failures, and dynam-icly scales and repacks services to achieve cost efficiency.As part of the framework, we introduce a decentralized scheduler that provides andmaintains durable allocations with low maintenance costs for data centers with dynamicworkloads. The scheduler assigns resources in response to virtual machine requests andmaintains the packing efficiency while taking into account migration costs, topologicalconstraints, and the risk of resource contention, as well as fluctuations of the backgroundload.We also introduce a scheduling algorithm that considers probabilistic failures as part ofthe planning for scheduling. The aim of the algorithm is to achieve an overall job reliabil-ity, in presence of correlated failures in a data center. To do so, we study the impacts ofstochastic and correlated failures on job reliability in a virtual data center. We specificallyfocus on correlated failures caused by power outages or failure of network components onjobs running large number of replicas of identical tasks.Additionally, we investigate the trade-offs between vertical and horizontal scaling. Theresult of the investigations is used to introduce a repacking technique to automatically man-age the capacity required by an elastic service. The repacking technique combines thebenefits of both scaling strategies to improve its cost-efficiency.<br>Datormoln har kommit att bli kraftfulla möjliggörare för många nya IT-tjänster. De ger tillgång till mycket storskaliga datorresurser på ett finkornigt och omedelbart sätt. För att tillhandahålla sådana resurser krävs att de underliggande datorcentren kan hantera sina resurser på ett tillförlitligt och effektivt sätt. Frågan hur man ska designa deras resurshanteringssystem är en stor utmaning då de ska kunna hantera mycket stora mängder heterogena resurser som i sin tur ska klara av vitt skilda typer av belastning, ofta med väldigt stora variationer över tid. Därtill ska de typiskt kunna möta en mängd olika krav och målsättningar för hur resurserna ska nyttjas. Autonomiska system kan med fördel användas för att realisera sådana system. Ett autonomt system innehåller ett antal autonoma element som automatiskt kan organisera och hantera sig själva utan stöd av externa regulatorer. Förmågan att hantera sig själva gör dem mycket lämpliga som komponenter i distribuerade system, vilka i sin tur kan bidra till snabbare beslutsprocesser, bättre skalbarhet och högre feltolerans. Denna avhandling fokuserar på algoritmer, modeller och tekniker för autonom hantering av jobb och virtuella resurser i datacenter. Vi introducerar ett decentraliserat resurshanteringssystem som automatiserar resursallokering och konsolidering, schedulerar jobb tillförlitligt med hänsyn till korrelerade fel, samt skalar resurser dynamiskt för att uppnå kostnadseffektivitet. Som en del av detta ramverk introducerar vi en decentraliserad schedulerare som allokerar resurser med hänsyn till att tagna beslut ska vara bra för lång tid och ge låga resurshanteringskostnader för datacenter med dynamisk belastning. Scheduleraren allokerar virtuella maskiner utifrån aktuell belastning och upprätthåller ett effektivt nyttjande av underliggande servrar genom att ta hänsyn till migrationskostnader, topologiska bivillkor och risk för överutnyttjande. Vi introducerar också en resursallokeringsalgoritm som tar hänsyn till korrelerade fel som ett led i planeringen. Avsikten är att kunna uppnå specificerade tillgänglighetskrav för enskilda tjänster trots uppkomst av korrelerade fel. Vi fokuserar främst på korrelerade fel som härrör från problem med elförsörjning och från felande nätverkskomponenter samt deras påverkan på jobb bestående av många identiska del-jobb. Slutligen studerar vi även hur man bäst ska kombinera horisontell och vertikal skalning av resurser. Resultatet är en process som ökar kostnadseffektivitet genom att kombinera de två metoderna och därtill emellanåt förändra fördelning av storlekar på virtuella maskiner.
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Sinha, Aman. "Memory management and transaction scheduling for large-scale databases /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
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Tayab, Usman Bashir. "Novel Forecasting and Scheduling for Microgrid Energy Management System." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/408937.
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The high penetration of renewable energy resources brought new challenges to the modern grid; therefore, new solutions and concepts need to be developed. The idea of a microgrid (MG) has been introduced to overcome the upcoming issues in modern grids. MG is a small-scale grid composed of renewable energy resources, energy storage, and load demand. MG makes decisions by itself and can operate in grid-connected or islanded mode depending on functionality. The microgrid energy management system (M-EMS) is the decision-making centre of MG. An M-EMS is composed of four modules which are known as forecasting, scheduling, data acquisition, and human-machine interface. However, the forecasting and scheduling modules are considered as the major modules among the four of them. The forecasting module is required in the M-EMS to predict the future power generation and consumption. The forecast data is the input to the scheduling module of M-EMS. Employing forecasting system in the M-EMS would increase the accuracy of the scheduling module. The scheduling module is responsible for controlling the power flow from/to the main grid. Additionally, it performs optimal day-ahead scheduling of available power generation resources to feed the load demand in a grid-connected MG for economical operation. Consequently, this research work presents four contributions in the area of M-EMS for grid-connected MG.
The first contribution of this research is to presents a hybrid strategy for short-term forecasting of load demand in M-EMS, which is a combination of best-basis stationary wavelet packet transform and the Harris hawks algorithm-based feedforward neural network. The Harris hawks algorithm is applied to the feedforward neural network as an alternative learning algorithm to optimized the weights and biases of neurons. The proposed model is applied for load demand prediction of the Queensland electric market and compared with existing competitive models. The simulation results prove the effectiveness of the proposed method.
The second contribution of this research is to design and proposed an ensemble forecasting strategy for solar PV power forecasting. The proposed ensemble strategy is based on a systematic combination of the tunicate swarm algorithm (TSA)-based multilayer perceptron neural network (TSA-MLPNN), TSA based least-square support vector machine (TSA-LSSVM), whales optimization algorithm (WOA) based MLPNN (WOAMLPNN), and WOA based LSSVM (WOA-LSSVM). The output of all the models is combined using the Bayesian model averaging method. The proposed ensemble strategy is validated through simulation of the real-time data of building N-78 Griffith University, Queensland. The simulation results demonstrated that the proposed strategy shows excellent performance in comparison with several existing competitive approaches.
The third contribution of this research is to propose an optimum scheduling strategy, using a weighted salp swarm algorithm for M-EMS, to perform the optimal scheduling of available power resources to meet consumer demand and minimize the operating cost of grid-connected MG. The performance of the proposed scheduling strategy is validated through simulation using MATLAB and compared with standard particle swarm optimization (PSO) based scheduling strategy. The comparison shows that the proposed strategy outperforms the PSO based strategy.
The final contribution of this research is to propose an M-EMS using an ensemble forecasting strategy and grey wolf optimization (GWO). In the proposed M-EMS, an ensemble forecasting strategy is used to accomplish short-term forecasting of PV power and load while the GWO is applied to perform the optimum scheduling of available power resources in grid-connected MG. A small-scale experiment is conducted using Raspberry Pi 3 B+ via python programming language to validate the effectiveness of the proposed M-EMS. The experimental results of the proposed M-EMS for the selected case prove the effectiveness of the proposed M-EMS. In summary, several forecasting and scheduling strategies have been proposed and validated for the M-EMS of a grid-connected MG.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Eng & Built Env<br>Science, Environment, Engineering and Technology<br>Full Text
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Jeffries, Thomas. "Optimising blood donation session scheduling in south east England." Thesis, University of Kent, 2015. https://kar.kent.ac.uk/54468/.
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It is essential that all countries operate a form of blood banking service, where blood is collected at donation sessions, stored and then distributed to local healthcare providers. It is imperative that these services are efficiently managed to ensure a safe supply of blood and that costs and wastages are kept minimal. Previous works in the area of blood management have focussed primarily on the perishable inventory problem and on routing blood deliveries to hospitals; there has been relatively little work focusing on scheduling blood donation sessions. The primary aim of this research is to provide a tool that allows the National Blood Service (the English and Welsh blood service) to schedule donation sessions so that collection targets are met in such a way that costs are minimised (the Blood Scheduling Problem). As secondary aims, the research identifies the key types of data that blood services should be collecting for this type of problem. Finally, various what-if scenarios are considered, specifically improv- ing donor attendance through paying donors and the proposed changes to the inter-donation times for male and female donors. The Blood Scheduling Problem is formulated as a Mixed Integer Linear Programming (MILP) problem and solved using a variable bound heuristic. Data from the South East of England is used to create a collection schedule, with all further analysis also being carried out on this data set. It was possible to make improvements to the number of units under collected in the current schedule, moreover the number of venues and panels operated could be reduced. Further- more, it was found that paying donors to donate was uneconomical. Finally, changing the inter-donation times could lead to a reduction in the number of shortfalls, even when demand was increased by as much as 20%. Though the model is specific to England and Wales, it can easily be adapted to other countries’ blood services. It is hoped that this model will provide blood services with a model to help them better schedule donation sessions and allow them to identify the data necessary to better understand their performance.
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Czogalla, Jens [Verfasser]. "Particle Swarm Optimization for Scheduling Problems / Jens Czogalla." Aachen : Shaker, 2010. http://d-nb.info/1122546289/34.
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Chan, Sze-hang, and 陳思行. "Competitive online job scheduling algorithms under different energy management models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/206690.
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Online flow-time scheduling is a fundamental problem in computer science and has been extensively studied for years. It is about how to design a scheduler to serve computer jobs with unpredictable arrival times and varying sizes and priorities so as to minimize the total flow time (better understood as response time) of jobs. It has many applications, most notable in the operating of server farms. As energy has become an important issue, the design of scheduler also has to take power management into consideration, for example, how to scale the speed of the processors dynamically. The objectives are orthogonal as one would prefer lower processor speed to save energy, yet a good quality of service must be retained. In this thesis, I study a few scheduling problems for energy and flow time in depth and give new algorithms to tackle them. The competitiveness of our algorithms is guaranteed with worst-case mathematical analysis against the best possible or hypothetical solutions.
In the speed scaling model, the power of a processor increases with its speed according to a certain function (e.g., a cubic function of speed). Among all online scheduling problems with speed scaling, the nonclairvoyant setting (in which the size of a job is not known during its execution) with arbitrary priorities is perhaps the most challenging. This thesis gives the first competitive algorithm called WLAPS for this setting.
In reality, it is not uncommon that during the peak-load period, some (low-priority) users have their jobs rejected by the servers. This triggers me to study more complicated scheduling algorithms that can strike a good balance among speed scaling, flow time and rejection penalty. Two new algorithms UPUW and HDFAC for different models of rejection penalty have been proposed and analyzed.
Last, but perhaps the most interesting, we study power management in large server farm environment in which the primary energy saving mechanism is to put some processors to sleep. Two new algorithms POOL and SATA have been designed to tackle jobs that cannot and can migrate among the processors, respectively. They are integrated algorithms that can consider speed scaling, job scheduling and processor sleep management together to optimize the energy usage and ow time simultaneously. These algorithms are again proven mathematically to be competitive even in the worst case.<br>published_or_final_version<br>Computer Science<br>Doctoral<br>Doctor of Philosophy
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Waldon, Jefferson L. "Maximizing wildlife benefits through hardwood timber harvest scheduling." Thesis, Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/80093.
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A computerized system for planning timber harvest to maximize habitat quality over time for a specified group of wildlife species was developed for upland oak forests of the Eastern United States. This system, called WILDWOOD for WILDiife/WOOD optimization system, is designed to run on a microcomputer. It utilizes a widely available database management system called PCFile III, Version 4, a forest growth and yield simulator adapted from work by Dale (1972), and a program developed by the author. The system utilizes 43 species-specific habitat value models developed by the author and others. Timber harvests in approximately one ha blocks (patch clearcut) are specified for each year to result in a maximum yearly average wildlife benefit figure. Wildlife benefits are defined as the product of a wildlife species value provided by the user, a forest-size-classspecific habitat value index, and the area of the cutting unit.
WILDWOOD was demonstrated on a 106 ha tract of upland oak forest on Havens Wildlife Management Area of the Virginia Commission of Game and Inland Fisheries. Six different objective functions were investigated and several model tests were conducted. Implications for the application of the WILDWOOD system were discussed, and it was concluded that, although the objectives of the study were met, the current WILDWOOD system should be modified to include smooth wildlife habitat succession models, at least a 150-year planning horizon, and capabilities for addressing cutting unit size, shape, and juxtaposition. Other possibilities for future revisions inclu~e modifying HEP (U.S. Fish and Wildlife Service) for use with WILDWOOD, and linking ageographic information system to WILDWOOD.<br>Master of Science
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Kenley, Gregory Grant. "An action management system for a distributed operating system." Thesis, Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/9153.
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Kaehkoenen, Kalle Esa Eelis. "Modelling activity dependencies for building construction project scheduling." Thesis, University of Reading, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336061.
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Elsaeiby, Aber. "Healthcare Operations Management: Models for Improving Productivity, Scheduling and Quality." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1449421673.
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Lane, R. "A problem-solving architecture for production scheduling." Thesis, Cranfield University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359570.
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Elkherbawy, Ahmed Abdelbasset. "Lean construction versus Project Management in road projects : scheduling comparison." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/668908.
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Lean Construction is regarded as an innovative approach of management for various types of projects in the field of construction. As much as it is currently applied in some countries, its expansion is inevitable, for better overall results are obtained and the projects’ objectives are met more precisely. Despite the fact that Lean Construction offers solutions to many problems occurring under the traditional management approach known as the Project Management (PM), the scope of its application is not as promising. Countries where Lean Construction is minimally applied include the United States of America and the United Kingdom besides other countries in Europe and Latin America. However, it is still not applied to a more exhaustive extent in these countries and is completely missing in many others around the world. This study primarily focuses on the application of Lean Construction to Infrastructure, specifically road projects; investigating Lean Construction solutions to the time wastes. Through conducting a case study research, this work focuses on investigating the impact of applying Last Planner System as a Lean Construction tool on the elimination of Non-Value Added (NVA) activities, that is, wastes in a highway project in Cairo, Egypt. This study includes a State of Art on both Project Management approach and Lean Construction. The study applies a comparative approach between the application of Project Management approach and Lean Construction in road projects. Hence, the researcher conducted different simulations of the studied road project, taking into account the two approaches (Project Management and Lean Construction), then obtaining the simulations results. Two parameters are used as comparison criteria: Percentage Plan Complete (PPC) and Percentage Activity Waste (PAW). The later (PAW) is a new parameter introduced by the researcher to investigate its results before/after applying the Lean Construction tools. Findings of the study support the research hypothesis that the application of Lean Construction approach to road projects enhances productivity through eliminating time-related wastes and decreasing the project duration. This research supports the argument that road projects can benefit greatly from the application of Lean Construction instead of the traditional approach.<br>Lean Construction es considerado como un enfoque innovador para la gestión de diversos tipos de proyectos en el campo de la construcción. Por más que se aplique actualmente en algunos países, su expansión es inevitable, ya que se obtienen mejores resultados generales y los objetivos de los proyectos se cumplen con mayor precisión. A pesar del hecho de que Lean Construction ofrece soluciones a muchos problemas que ocurren bajo el enfoque de administración tradicional conocido como Gestión de Proyectos (Project Management, PM), el alcance de su aplicación no es tan prometedor. Los países en los que se aplica mínimamente el Lean Construction son los Estados Unidos de América y el Reino Unido, además de otros países de Europa y América Latina. Sin embargo, todavía no se aplica de manera más exhaustiva en estos países y está completamente ausente en muchos otros en todo el mundo. Este estudio se centra principalmente en la aplicación de el Lean Construction a Infraestructura, específicamente en proyectos viales; Investigando soluciones de Lean Construction para los desperdicios del tiempo. A través de la realización de una investigación de estudio de caso, este trabajo se enfoca en investigar el impacto de la aplicación del Sistema Last Planner como una herramienta Lean Construction en la eliminación de actividades sin valor agregado (NVA), es decir, desechos en un proyecto vial en El Cairo, Egipto. Este estudio incluye un estado del arte tanto en el enfoque de gestión tradicional de proyectos Project Management como en Lean Construction. El estudio se aplica a un enfoque comparativo entre la aplicación del enfoque de el Project Management y el Lean Construction en proyectos viales. Por lo tanto, el investigador realizó diferentes simulaciones del proyecto de carretera estudiado, teniendo en cuenta los dos enfoques (Project Management y Lean Construction), y luego obtuvo los resultados de las simulaciones. Se utilizan dos parámetros como criterios de comparación: Plan de porcentaje completado (PPC) y Porcentaje de residuos de actividad (PAW). El último (PAW) es un nuevo parámetro introducido por el investigador para investigar sus resultados antes / después de aplicar las herramientas de el Lean Construction. Los hallazgos del estudio apoyan la hipótesis de la investigación de que la aplicación del enfoque de Lean Construction a los proyectos viales aumenta la productividad al eliminar los desechos relacionados con el tiempo y disminuir la duración del proyecto. Esta investigación apoya el argumento de que los proyectos viales pueden mejorarse en gran medida con la aplicación de el Lean Construction en lugar del enfoque tradicional el Project Management.
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Buyya, Rajkumar 1970. "Economic-based distributed resource management and scheduling for grid computing." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8760.
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Lu, Peng. "Application profiling and resource management for MapReduce." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/13969.
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Scale of data generated and processed is exponential growth in the Big Data ear. It poses a challenge that is far beyond the goal of a single computing system. Processing such vast amount of data on a single machine is impracticable in term of time or cost. Hence, distributed systems, which can harness very large clusters of commodity computers and processing data within restrictive time deadlines, are imperative. In this thesis, we target two aspects of distributed systems: application profiling and resource management. We study a MapReduce system in detail, which is a programming paradigm for large scale distributed computing, and presents solutions to tackle three key problems. Firstly, this thesis analyzes the characteristics of jobs running on the MapReduce system to reveal the problem—the Application scope of MapReduce has been extended beyond the original design goal that was large-scale data processing. This problem enables us to present a Workload Characteristic Oriented Scheduler (WCO), which strives for co-locating tasks of possibly different MapReduce jobs with complementing resource usage characteristics. Secondly, this thesis studies the current job priority mechanism focusing on resource management. In the MapReduce system, job priority only exists at scheduling level. High priority jobs are placed at the front of the scheduling queue and dispatched first. Resource, however, is fairly shared among jobs running at the same worker node without any consideration for their priorities. In order to resolve this, this thesis presents a non-intrusive slot layering solution, which dynamically allocates resource between running jobs based on their priority and efficiently reduces the execution time of high priority jobs while improves overall throughput. Last, based on the fact of underutilization of resource at each individual worker node, this thesis propose a new way, Local Resource Shaper (LRS), to smooth resource consumption of each individual job by automatically tuning the execution of concurrent jobs to maximize resource utilization while minimizing resource contention.
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Khosravi, Banafsheh. "Train scheduling with application to the UK rail network." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/364584/.
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Nowadays, transforming the railway industry for better performance and making the best usage of the current capacity are the key issues in many countries. Operational research methods and in particular scheduling techniques have a substantial potential to offer algorithmic solutions to improve railway operation and control. This thesis looks at train scheduling and rescheduling problems in a microscopic level with regard to the track topology. All of the timetable components are fixed and we aim to minimize delay by considering a tardiness objective function and only allowing changes to the order and to the starting times of trains on blocks. Various operational and safety constraints should be considered. We have achieved further developments in the �eld including generalizations to the existing models in order to obtain a generic model that includes important additional constraints. We make use of the analogy between the train scheduling problem and job shop scheduling problem. The model is customized to the UK railway network and signaling system. Introduced solution methods are inspired by the successful results of the shifting bottleneck to solve the job shop scheduling problems. Several solution methods such as mathematical programming and different variants of the shifting bottleneck are investigated. The proposed methods are implemented on a real-world case study based on London Bridge area in the South East of the UK. It is a dense network of interconnected lines and complicated with regard to stations and junctions structure. Computational experiments show the effciency and limitations of the mathematical programming model and one variant of the proposed shifting bottleneck algorithms. This study also addresses train routing and rerouting problems in a mesoscopic level regarding relaxing some of the detailed constraints. The aim is to make the best usage of routing options in the network to minimize delay propagation. In addition to train routes, train entry times and orders on track segment are defined. Hence, the routing and scheduling decisions are combined in the solutions arising from this problem. Train routing and rerouting problems areformulated as modified job shop problems to include the main safety and operational constraints. Novel shifting bottleneck algorithms are provided to solve the problem. Computational results are reported on the same case study based on London Bridge area and the results show the efficiency of one variant of the developed shifting bottleneck algorithms in terms of solution quality and runtime.
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Knight, Roger Alan. "Optimisation methods for staff scheduling and rostering : an employee-friendly approach." Thesis, City University London, 2008. http://openaccess.city.ac.uk/12268/.
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The growth in the global call centre industry over the last twenty years has been huge. The main motivating factor for businesses to introduce call centres as their main vehicle for handling customer contacts has been that call centres are inherently efficient. Since the mid-1980's, UK businesses have sought to establish competitive advantage by using call centres to reduce the cost of managing their customer contacts. Over the last decade or so, however, an alternative strategy has emerged based not on cost-reduction and efficiency, but on revenue generation and service quality. This new strategy places high value on customer and staff retention. This thesis is concerned with the operations management task of employee rostering. We argue that traditional models for producing rosters for call centre employees are designed to support the older efficiency-based culture, and are inappropriate for call centres adopting the more recent quality-based culture. We show how the use of methods and models drawn from conflicting management philosophies contributes to the high level of employee turnover, and inhibits the drive for service quality. Our primary contributions are to identify a set of rostering goals which reflect the interests of the employees, and to quantitatively represent these goals in a system of mathematical rostering models designed to support the revenue generation strategy. Our models are implemented using the robust Mixed Integer Programming methodology. In addition, we adapt our model to address the related problem of nurse rostering, and solve two benchmark problems to optimality. We demonstrate that our model generates rosters of a higher quality than the alternatives, at no additional cost.
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Witt, Carl Philipp. "Predictive Resource Management for Scientific Workflows." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21608.
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Um Erkenntnisse aus großen Mengen wissenschaftlicher Rohdaten zu gewinnen, sind komplexe Datenanalysen erforderlich. Scientific Workflows sind ein Ansatz zur Umsetzung solcher Datenanalysen. Um Skalierbarkeit zu erreichen, setzen die meisten Workflow-Management-Systeme auf bereits existierende Lösungen zur Verwaltung verteilter Ressourcen, etwa Batch-Scheduling-Systeme. Die Abschätzung der Ressourcen, die zur Ausführung einzelner Arbeitsschritte benötigt werden, wird dabei immer noch an die Nutzer:innen delegiert. Dies schränkt die Leistung und Benutzerfreundlichkeit von Workflow-Management-Systemen ein, da den Nutzer:innen oft die Zeit, das Fachwissen oder die Anreize fehlen, den Ressourcenverbrauch genau abzuschätzen.
Diese Arbeit untersucht, wie die Ressourcennutzung während der Ausführung von Workflows automatisch erlernt werden kann. Im Gegensatz zu früheren Arbeiten werden Scheduling und Vorhersage von Ressourcenverbrauch in einem engeren Zusammenhang betrachtet. Dies bringt verschiedene Herausforderungen mit sich, wie die Quantifizierung der Auswirkungen von Vorhersagefehlern auf die Systemleistung.
Die wichtigsten Beiträge dieser Arbeit sind:
1. Eine Literaturübersicht aktueller Ansätze zur Vorhersage von Spitzenspeicherverbrauch mittels maschinellen Lernens im Kontext von Batch-Scheduling-Systemen.
2. Ein Scheduling-Verfahren, das statistische Methoden verwendet, um vorherzusagen, welche Scheduling-Entscheidungen verbessert werden können.
3. Ein Ansatz zur Nutzung von zur Laufzeit gemessenem Spitzenspeicherverbrauch in Vorhersagemodellen, die die fortwährende Optimierung der Ressourcenallokation erlauben. Umfangreiche Simulationsexperimente geben Einblicke in Schlüsseleigenschaften von Scheduling-Heuristiken und Vorhersagemodellen.
4. Ein Vorhersagemodell, das die asymmetrischen Kosten überschätzten und unterschätzten Speicherverbrauchs berücksichtigt, sowie die Folgekosten von Vorhersagefehlern einbezieht.<br>Scientific experiments produce data at unprecedented volumes and resolutions. For the extraction of insights from large sets of raw data, complex analysis workflows are necessary. Scientific workflows enable such data analyses at scale. To achieve scalability, most workflow management systems are designed as an additional layer on top of distributed resource managers, such as batch schedulers or distributed data processing frameworks. However, like distributed resource managers, they do not automatically determine the amount of resources required for executing individual tasks in a workflow. The status quo is that workflow management systems delegate the challenge of estimating resource usage to the user. This limits the performance and ease-of-use of scientific workflow management systems, as users often lack the time, expertise, or incentives to estimate resource usage accurately.
This thesis is an investigation of how to learn and predict resource usage during workflow execution. In contrast to prior work, an integrated perspective on prediction and scheduling is taken, which introduces various challenges, such as quantifying the effects of prediction errors on system performance.
The main contributions are:
1. A survey of peak memory usage prediction in batch processing environments. It provides an overview of prior machine learning approaches, commonly used features, evaluation metrics, and data sets.
2. A static workflow scheduling method that uses statistical methods to predict which scheduling decisions can be improved.
3. A feedback-based approach to scheduling and predictive resource allocation, which is extensively evaluated using simulation. The results provide insights into the desirable characteristics of scheduling heuristics and prediction models.
4. A prediction model that reduces memory wastage. The design takes into account the asymmetric costs of overestimation and underestimation, as well as follow up costs of prediction errors.
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Nuchprayoon, Somboon. "On power scheduling and strategic behavior in electricity markets." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13532.
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White, Denise L. "Operational Planning and Scheduling in the Outpatient Clinic Environment." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1276527552.
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Wang, R. "Berth scheduling at seaports : meta-heuristics and simulation." Thesis, Liverpool John Moores University, 2018. http://researchonline.ljmu.ac.uk/9652/.
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This research aims to develop realistic solutions to enhance the efficiency of port operations. By conducting a comprehensive literature review on logistic problems at seaports, some important gaps have been identified for the first time. The following contributions are made in order to close some of the existing gaps. Firstly, this thesis identifies important realistic features which have not been well-studied in current academic research of berth planning. This thesis then aims to solve a discrete dynamic Berth allocation problem (BAP) while taking tidal constraints into account. As an important feature when dealing with realistic scheduling, changing tides have not been well-considered in BAPs. To the best of our knowledge, there is no existing work using meta-heuristics to tackle the BAP with multiple tides that can provide feasible solutions for all the test cases. We propose one single-point meta-heuristic and one population-based meta-heuristic. With our algorithms, we meet the following goals: (i) to minimise the cost of all vessels while staying in the port, and (ii) to schedule available berths for the arriving vessels taking into account a multi-tidal planning horizon. Comprehensive experiments are conducted in order to analyse the strengths and weaknesses of the algorithms and compare with both exact and approximate methods. Furthermore, lacking tools for examining existing algorithms for different optimisation problems and simulating real-world scenarios is identified as another gap in this study. This thesis develops a discrete-event simulation framework. The framework is able to generate test cases for different problems and provide visualisations. With this framework, contributions include assessing the performance of different algorithms for optimisation problems and benchmarking optimisation problems.
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Ullo, Silvia Liberata. "Evaluation of scheduling strategies in a semiconductor wafer fab using simulation." Thesis, Massachusetts Institute of Technology, 1992. https://hdl.handle.net/1721.1/128456.
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Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1992.<br>Includes bibliographical references (leaves 105-107).<br>by Silvia Liberata Ullo.<br>Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1992.
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Kassam, Alla-Eldin Hassan. "Studies in artificial intelligence applied to job scheduling." Thesis, University of Strathclyde, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.291955.
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Batun, Sakine. "Machine Scheduling With Preventive Maintenances." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607354/index.pdf.
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In manufacturing environments, machines are usually subject to down periods due to various reasons such as preventive maintenance activities, pre-accepted jobs and pre-known material shortages. Among these reasons, preventive maintenance, which is defined as the pre-planned maintenance activities to keep the machine in its operating state, has gained much more importance in recent years.
In this thesis, we consider the single machine total flow time problem where the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a number of optimality properties together with the upper and lower bounding procedures. Using these mechanisms, we build a branch and bound algorithm to find the optimal solution of the problem. Our extensive computational study on randomly generated test instances shows that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times.
We also study a two-alternative maintenance planning problem with minor and major maintenances. We give an optimizing algorithm to find the timing of the maintenances, when the job sequence is fixed.
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Kiciroglu, Ahmet. "Scheduling With Discounted Costs." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1208321/index.pdf.
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Majority of the studies in the scheduling literature is devoted to time based performance measures. In this thesis, we develop a model that considers monetary issues in single machine scheduling environments. We assume all the jobs should be completed by a common due date. An early revenue is earned if the completion time is before or on the due date, and a tardy revenue is gained if the job is completed after the due date. We consider restricted and unrestricted due date versions of the problem. Our objective is the maximization of the net present value of all revenues.
We first investigate some special cases of the problem, and present polynomial time algorithms to solve them. Then, we develop branch and bound algorithms with lower and upper bounding mechanisms. Computational experiments have shown that the branch and bound algorithms can solve large-sized problems in reasonable times.
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Bai, Sherman Xiewei. "Scheduling manufacturing systems with work-in-process inventory control." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13477.
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Qian, Fei. "Scheduling problems for fractional airlines." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/39641.
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A column generation based approach is proposed to solve scheduling problems for fractional airlines
efficiently and return near optimal schedules. Crew tours are building blocks of our approach, and
our approach is focused on exploring more feasible tours than other approaches. In particular, all
elements of a crew tour are optimized during the preparation and tour generation procedures.
Moreover, time windows of customer-requested flights are handled exactly, and generalized to time
window and crew time window of duties and tours. Furthermore, time windows of tours are contained
in the MIP formulation to ensure more feasible connections between tours.
In the pricing subproblem, an efficient constrained shortest path algorithm is proposed, which is
necessary for our model and also provides extensibility for incorporating more complex constraints
in the future. Computational results of our model show very small optimality gaps and consistent
improvements over the model used in practice. Moreover, restricted versions of our model that have
fast running time are provided, thus very desired in the case that running time has more priority
than solution quality. In order to understand the demand, data mining of demand data is presented
and analyzed. Moreover, a recovery model is proposed to deal with unscheduled maintenance in
practice, by reserving airplanes and crews in the model. Computational experiments show the
advantage of the recovery model, in the case of simulated unscheduled maintenance and comparing to
models without recovery considerations.
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Pan, Hongqi 1961. "Fuzzy multi-mode resource-constrained project scheduling." Monash University, School of Business Systems, 2003. http://arrow.monash.edu.au/hdl/1959.1/5735.
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