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Journal articles on the topic 'Mathematical optimization. Algorithms. Network analysis (Planning)'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Nitola, Alejandra, Jennyfer Marin, and Sergio Rivera. "Scheduling of a Microgrid with High Penetration of Electric Vehicles Considering Congestion and Operations Costs." Vehicles 3, no. 3 (2021): 578–94. http://dx.doi.org/10.3390/vehicles3030035.

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This paper reviews the impact that can be presented by the immersion of generation sources and electric vehicles into the distribution network, with a technical, operational and commercial approach, given by the energy transactions between customer and operator. This requires a mathematical arrangement to identify the balance between congestion and the operating cost of a microgrid when the operation scheduling of the system a day ahead of horizon time it is required. Thus, this research is directed to the solution, using heuristic algorithms, since they allow the non-convex constraints of the

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Fuso, Flavia, Maria C. Cunha, and Gianfranco Becciu. "Functional Feasibility in Optimal Evaluation of Water Distribution Network Performances." Water 12, no. 12 (2020): 3404. http://dx.doi.org/10.3390/w12123404.

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The traditional approach for the optimization of water distribution networks (WDNs) does not always lead to consistent solutions from an operational point of view. The latest optimization algorithms identify solutions that are “the best solutions” in mathematical terms but that can be less than robust against changes in operating conditions, resulting in the worst case in hydraulically infeasible configurations. Thus, this paper aims to provide a methodology that can synthesize the network performance capabilities under the change in operating conditions with two convergent strategies. The fir

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Нырков, Д., D. Nyrkov, Александр Стариков, and Aleksandr Starikov. "Analysis of Advanced Algorithms Master Production Schedule for Custom Manufacture of Furniture." Forestry Engineering Journal 7, no. 3 (2017): 299–306. http://dx.doi.org/10.12737/article_59c2124049cd45.48567850.

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The article discusses the algorithms employed in automated systems for master production scheduling in the applicability of their produce-to-order furniture. Small batch and custom production of furniture occupies a significant market share, as we do, and in the countries of Western Europe. Also, it is a prospective direction of development for other industries, focused on the end user. Most of the existing national planning systems designed for large-scale and mass production, in which the main role takes enterprise performance. Therefore, the main indicator, which is used by the optimization

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Martínez-Bahena, Beatriz, Marco Cruz-Chávez, Erika Ávila-Melgar, Martín Cruz-Rosales, and Rafael Rivera-Lopez. "Using a Genetic Algorithm with a Mathematical Programming Solver to Optimize a Real Water Distribution System." Water 10, no. 10 (2018): 1318. http://dx.doi.org/10.3390/w10101318.

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This research proposes a genetic algorithm that provides a solution to the problem of deficient distribution of drinking water via the current hydraulic network in the neighborhood “Fraccionamiento Real Montecasino” (FRM), in Huitzilac, Morelos, Mexico. The proposed solution is the addition of new elements to the FRM network. The new elements include storage tanks, pipes, and pressure-reducing valves. To evaluate the constraint satisfaction model of mass and energy conservation, the hydraulic EPANET solver (HES) is used with an optimization model to minimize the total cost of changes in the ne

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Dobrynin, Alexey Sergeyevich, Stanislav Matveevich Kulakov, and Alexander Sergeyevich Koynov. "BUILDING UP SCHEDULES IN MULTIPROJECT DESIGN MANAGEMENT SYSTEMS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2021, no. 3 (2021): 105–14. http://dx.doi.org/10.24143/2072-9502-2021-3-105-114.

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The article focuses on the problem of algorithmizing the process of building schedules in various spheres of human activity by using the modern mathematical apparatus, as well as achievements in the field of systems analysis, game theory, and graph theory. Nowadays, there have been analyzed and determined the boundaries of the effective application of many well-known heuristic and metaheuristic algorithms, which have shown good results in practice. However, despite the achievements in the discrete optimization, scheduling and network planning, the new problems of drawing up so-called coordinat

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Chai, Huo, Ruichun He, Changxi Ma, Cunjie Dai, and Kun Zhou. "Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load." Discrete Dynamics in Nature and Society 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9685125.

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Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL) are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting Genetic Algorithm II (NSGA-II) is designed to obtain candidate transport paths. Second, with analysis

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Wu, Daqing, Jiazhen Huo, Gefu Zhang, and Weihua Zhang. "Minimization of Logistics Cost and Carbon Emissions Based on Quantum Particle Swarm Optimization." Sustainability 10, no. 10 (2018): 3791. http://dx.doi.org/10.3390/su10103791.

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This paper aims to simultaneously minimize logistics costs and carbon emissions. For this purpose, a mathematical model for a three-echelon supply chain network is created considering the relevant constraints such as capacity, production cost, transport cost, carbon emissions, and time window, which will be solved by the proposed quantum-particle swarm optimization algorithm. The three-echelon supply chain, consisting of suppliers, distribution centers, and retailers, is established based on the number and location of suppliers, the transport method from suppliers to distribution centers, and

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D’Emidio, Mattia. "Faster Algorithms for Mining Shortest-Path Distances from Massive Time-Evolving Graphs." Algorithms 13, no. 8 (2020): 191. http://dx.doi.org/10.3390/a13080191.

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Computing shortest-path distances is a fundamental primitive in the context of graph data mining, since this kind of information is essential in a broad range of prominent applications, which include social network analysis, data routing, web search optimization, database design and route planning. Standard algorithms for shortest paths (e.g., Dijkstra’s) do not scale well with the graph size, as they take more than a second or huge memory overheads to answer a single query on the distance for large-scale graph datasets. Hence, they are not suited to mine distances from big graphs, which are b

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Chen, Lina, Longxi Han, Hong Ling, et al. "Allocating Water Environmental Capacity to Meet Water Quality Control by Considering Both Point and Non-Point Source Pollution Using a Mathematical Model: Tidal River Network Case Study." Water 11, no. 5 (2019): 900. http://dx.doi.org/10.3390/w11050900.

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Based on the principles of fairness and feasibility, a nonlinear optimization allocation method for pollutants was developed based on controlled section water quality standards, considering the synergetic influence of point and surface sources. The maximum allowable emission of pollutants from point and surface sources were taken as the objective function. The water quality attainment rate of controlled sections, the control requirements of pollution sources, and technical parameters of pollution control engineering were taken as constraints. A nonlinear optimization allocation model was estab

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Meng, Ming, Yanan Fu, Huifeng Shi, and Xinfang Wang. "A Small-Sample Adaptive Hybrid Model for Annual Electricity Consumption Forecasting." Mathematical Problems in Engineering 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/7427131.

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Annual electricity consumption forecasting is one of the important foundations of power system planning. Considering that the long-term electricity consumption curves of developing countries usually present approximately exponential growth trends and linear and accelerated growth rate trends may also appear in certain periods, this paper first proposes a small-sample adaptive hybrid model (AHM) to extrapolate the above curves. The iterative trend extrapolation equation of the proposed model can simulate the linear, exponential, and steep trends adaptively at the same time. To estimate the equa

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Butko, T. V., V. M. Prokhorov, L. O. Parkhomenko, and A. O. Prokopov. "Improvement of Technology of Passenger Intermodal Transportation with Involvement of Railway Transport in the Conditions of Tourism Development." Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, no. 1(91) (February 15, 2021): 37–50. http://dx.doi.org/10.15802/stp2021/228106.

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Purpose. The main purpose of the authors is to define and methodically substantiate the ways to increase the efficiency of intermodal passenger transportations with the involvement of high-speed trains as an auxiliary mode of transport in terms of sea and river tourism. Methodology. In the process of research the following was used: the method of factor analysis – to determine the factors influencing the attractiveness of tourist travel using high-speed trains as ancillary transport; method of skipping stops – to increase the efficiency of using high-speed trains as an auxiliary mode of transp

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Zeng, Mingbin, Xu Yang, Mengxing Wang, and Bangjiang Xu. "Application of Angle Related Cost Function Optimization for Dynamic Path Planning Algorithm." Algorithms 11, no. 8 (2018): 127. http://dx.doi.org/10.3390/a11080127.

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In recent years, Intelligent Transportation Systems (ITS) have developed a lot. More and more sensors and communication technologies (e.g., cloud computing) are being integrated into cars, which opens up a new design space for vehicular-based applications. In this paper, we present the Spatial Optimized Dynamic Path Planning algorithm. Our contributions are, firstly, to enhance the effective of loading mechanism for road maps by dividing the connected sub-net, and building a spatial index; and secondly, to enhance the effect of the dynamic path planning by optimizing the search direction. We u

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Zhang, Tao, Yue Wang, Xin Jin, and Shan Lu. "Integration of Production Planning and Scheduling Based on RTN Representation under Uncertainties." Algorithms 12, no. 6 (2019): 120. http://dx.doi.org/10.3390/a12060120.

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Production planning and scheduling are important bases for production decisions. Concerning the traditional modeling of production planning and scheduling based on Resource-Task Network (RTN) representation, uncertain factors such as utilities are rarely considered as constraints. For the production planning and scheduling problem based on RTN representation in an uncertain environment, this paper formulates the multi-period bi-level integrated model of planning and scheduling, and introduces the uncertainties of demand and utility in planning and scheduling layers respectively. Rolling horizo

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Sun, Wei, and Xingyan Chang. "An Improved Harmony Search Algorithm for Power Distribution Network Planning." Journal of Electrical and Computer Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/753712.

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Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS) algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network pl

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Bartonek, Dalibor, Jiri Bures, and Otakar Svabensky. "Optimized GNSS RTK measurement planning for effective point occupation via heuristic analysis." Engineering Computations 34, no. 1 (2017): 90–104. http://dx.doi.org/10.1108/ec-11-2015-0352.

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Purpose This paper aims to deal with the formulation of the technological principle for precise positioning using global navigation satellite systems (GNSS) in railway engineering during construction and maintenance of a railway line and its spatial position. Solution of optimal route is based on finding the shortest Hamiltonian path in the graph method with additional conditions in nodes. Design/methodology/approach The core of the algorithm is a dynamic data structure which is based on events list. The optimization of field measurement solves the time demands and brings economic effectivenes

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Li, Hong Kai, Ming Jun Lv, and Jian Guo Liu. "Distribution Substation Site Planning Method Summary and Discussion." Applied Mechanics and Materials 620 (August 2014): 158–61. http://dx.doi.org/10.4028/www.scientific.net/amm.620.158.

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The substation location is an important part of network planning . In this Paper, the optimal siting and site optimization mathematical model of classification are introduced , and the methods used in substation siting analyze many algorithms for a more comprehensive overview ; Finally,we offer some suggestions for the method of substation power market environment devlopment research .

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Shorikov, Andrey. "Optimization of adaptive network economic and mathematical modeling of business planning process control." Economics and the Mathematical Methods 57, no. 3 (2021): 110. http://dx.doi.org/10.31857/s042473880016413-3.

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The article is devoted to the application of economic and mathematical models of business planning management based on the use of the feedback principle. As the objective function (evaluation toolkit) of the task, the value of the execution time of the entire business project, which must be minimized, is considered. To solve this problem, it is proposed to form a class of admissible strategies for optimal adaptive control of the implementation process; as well as a specific business project using network economic and mathematical modeling is worked out. Within the limits of these strategies, t

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Liu, Xu, and Cui Lian Tang. "A New Transmission Network Planning Method with Consideration of Transmission Cost." Applied Mechanics and Materials 316-317 (April 2013): 132–35. http://dx.doi.org/10.4028/www.scientific.net/amm.316-317.132.

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Transmission planning is a complex optimization problem with multiple deciding variables and restrictions. The mathematical model is non-linear, discrete, multi-objective and dynamic. It becomes complicated as the system grows. So the algorithm adopted affects the results of planning directly. In this paper, a fast non-dominated sorting genetic algorithm (NSGA-II) is employed. The results indicate that NSGA-II has some advantages compared to the traditional genetic algorithms. In transmission planning, NSGA-II is feasible, flexible and effective.

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Liu, Bin, Ren Hui Kong, and Xiao Bing Xiao. "Reactive Power Optimization in District Power System." Advanced Materials Research 805-806 (September 2013): 751–55. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.751.

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Numerical optimization algorithms and heuristic optimization algorithms in reactive power optimization have been introduced. Analysis of the reactive power balance and the compensation, reactive power optimization mathematical model has been studied. Finally, it takes the least net loss as the object functions to optimize the regional power grid reactive power by genetic algorithm. Optimization results show that this method can effectively reduce network loss, and energy-saving effect is remarkable.

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Yang, Yanhua, and Ligang Yao. "Optimization Method of Power Equipment Maintenance Plan Decision-Making Based on Deep Reinforcement Learning." Mathematical Problems in Engineering 2021 (March 15, 2021): 1–8. http://dx.doi.org/10.1155/2021/9372803.

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The safe and reliable operation of power grid equipment is the basis for ensuring the safe operation of the power system. At present, the traditional periodical maintenance has exposed the abuses such as deficient maintenance and excess maintenance. Based on a multiagent deep reinforcement learning decision-making optimization algorithm, a method for decision-making and optimization of power grid equipment maintenance plans is proposed. In this paper, an optimization model of power grid equipment maintenance plan that takes into account the reliability and economics of power grid operation is

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Gomes, Phillipe Vilaça, and João Tomé Saraiva. "Comparative Analysis of Constructive Heuristic Algorithms for Transmission Expansion Planning." U.Porto Journal of Engineering 2, no. 2 (2018): 55–64. http://dx.doi.org/10.24840/2183-6493_002.002_0006.

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Transmission Expansion Planning (TEP) is a complex optimization problem that has the purpose of determining how the transmission capacity of a network should be enlarged, satisfying the increasing demand. This problem has combinatorial nature and different alternative plans can be designed so that many algorithms can converge towards local optima. This feature drives the development of tools that combine high robustness and low computational effort. This paper presents a comparative analysis and a detailed review of the main Constructive Heuristic Algorithms (CHA) used in the TEP problem. This

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Verma, Ashu R., P. K. Bijwe, and B. Panigrahi. "A Comparative Study of Metaheuristic Methods for Transmission Network Expansion Planning." International Journal of Applied Evolutionary Computation 1, no. 4 (2010): 71–91. http://dx.doi.org/10.4018/jaec.2010100104.

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Transmission network expansion planning is a very complex and computationally demanding problem due to the discrete nature of the optimization variables. This complexity has increased even more in a restructured deregulated environment. In this regard, there is a need for development of more rigorous optimization techniques. This paper presents a comparative analysis of three metaheuristic algorithms known as Bacteria foraging (BF), Genetic algorithm (GA), and Particle swarm optimization (PSO) for transmission network expansion planning with and without security constraints. The DC power flow

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Li, Honglei, and Yi Lu. "A Bilevel Programming Location Approach to Regional Waste Electric and Electronic Equipment Collection Centers: A Study in China." Mathematical Problems in Engineering 2021 (January 25, 2021): 1–10. http://dx.doi.org/10.1155/2021/6669989.

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As one of the largest markets of electronic and electric equipment, China has not completely established the formal recycling system of WEEE compared with the developed countries. As a result, China is facing the huge challenge of resource waste and water/soil environmental pollution. In this paper, according to the current regulations on WEEE recycling and disposal issued by Chinese government, the business model of the Chinese WEEE recycling system was designed, and a bilevel programming-based model was proposed to help the disposal factories to establish the regional efficient and economica

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Yang, Ting, Zhiyong Huang, Haibo Pen, and Yajian Zhang. "Optimal Planning of Communication System of CPS for Distribution Network." Journal of Sensors 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/9303989.

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IoT is the technical basis to realize the CPS (Cyber Physical System) for distribution networks, with which the complex system becomes more intelligent and controllable. Because of the multihop and self-organization characteristics, the large-scale heterogeneous CPS network becomes more difficult to plan. Using topological potential theory, one of typical big data analysis technologies, this paper proposed a novel optimal CPS planning model. Topological potential equalization is considered as the optimization objective function in heterogeneous CPS network with the constraints of communication

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Zhu, Dan-dan, and Jun-qing Sun. "The Path Optimization Algorithm of Car Navigation System considering Node Attributes under Time-Invariant Network." Mobile Information Systems 2021 (January 4, 2021): 1–20. http://dx.doi.org/10.1155/2021/2963092.

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Vehicle path planning plays a key role in the car navigation system. In actual urban traffic, the time spent at intersections accounts for a large proportion of the total time and cannot be ignored. Therefore, studying the shortest path planning problem considering node attributes has important practical significance. In this article, we study the vehicle path planning problem in time-invariant networks, with the minimum travel time from the starting node to the destination node as the optimization goal (including node time cost). Based on the characteristics of the problem, we construct the m

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Luong, Ngoc Hoang, Han La Poutré, and Peter A. N. Bosman. "Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning." Evolutionary Computation 26, no. 3 (2018): 471–505. http://dx.doi.org/10.1162/evco_a_00209.

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This article tackles the Distribution Network Expansion Planning (DNEP) problem that has to be solved by distribution network operators to decide which, where, and/or when enhancements to electricity networks should be introduced to satisfy the future power demands. Because of many real-world details involved, the structure of the problem is not exploited easily using mathematical programming techniques, for which reason we consider solving this problem with evolutionary algorithms (EAs). We compare three types of EAs for optimizing expansion plans: the classic genetic algorithm (GA), the esti

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Zhang, Jing. "Solution to Holes Machining Path Planning by Intelligence Computation." Applied Mechanics and Materials 319 (May 2013): 491–96. http://dx.doi.org/10.4028/www.scientific.net/amm.319.491.

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The rapid development of electronic information industry has posed serious challenges to the electronics manufacturing technology and intense competition in the market. For the most basic parts of electronic components - holes of the printed circuit board processing efficiency issues need to be resolved, the machining tool path optimization techniques. Optimize holes machining path reducing tool movement time is an effective way to improve production efficiency. Machining path optimization problem is transformed into a traveling salesman problem, shortest processing path established path optim

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Kou, Zheng, and Man Zhang. "LRP Model and Algorithm of Expressway Logistics Network Planning Based on Internet of Things." Mobile Information Systems 2021 (September 18, 2021): 1–12. http://dx.doi.org/10.1155/2021/5648330.

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With the continuous improvement of the expressway logistics network, the location-routing problems (LRP) have become the obstacle to be overcome in the development of related industries. Based on the needs of modernization, in the era of the Internet of Things, classic traffic path planning algorithms can no longer meet the increasingly diverse needs, and related research results are not ideal. To reduce logistics costs and meet customer needs, this paper studies transportation route planning models and algorithms based on Internet of Things technology and particle swarm optimization. Firstly,

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Slavutskaya, Elena, and Leonid Slavutskii. "PRETEEN AGE: THE ANALYSIS OF THE MULTILEVEL PSYCHO-DIAGNOSTIC DATA BASED ON NEURAL NETWORK MODELS." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 5 (May 25, 2018): 455. http://dx.doi.org/10.17770/sie2018vol1.3348.

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The use of the artificial neural network (ANN) models for vertical system analysis of psycho-diagnostic data is suggested. It is shown that the ANN training, as the problem of nonlinear multi-parameter optimization, allows to create effective algorithms for the psycho-diagnostic data processing when the results of psychological testing for the different level’s characteristics have different numerical scales. On the example of processing the author's data of psycho-diagnostics (preadolescent schoolchildren), it is shown that neural network models can be used to estimate latent (hidden) connect

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Huang, Xiaohui, Shuxia Zheng, Shilong Li, Jinxiang Wu, and Graham Spence. "Scheduling Problem of Biochemical Analyzer and Exploration of Neural Network-Greedy Algorithm." Journal of Medical Imaging and Health Informatics 10, no. 8 (2020): 1912–18. http://dx.doi.org/10.1166/jmihi.2020.3120.

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The mathematical model of biochemical analysis system was established based on neural network-greedy algorithm. The optimal task scheduling sequence was solved by neural network algorithm. At the same time, the local optimization was obtained by combining greedy algorithm. In this way, the task scheduling problem in biochemical analyzer was transformed into a mathematical problem, and the mathematical model of scheduling algorithm was established. On the platform of MATLAB, eight groups of simulation tests were carried out on the same task scheduling problem using the neural network-greedy sch

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Ozguven, Eren Erman, and Kaan Ozbay. "Simultaneous Perturbation Stochastic Approximation Algorithm for Solving Stochastic Problems of Transportation Network Analysis." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (2008): 12–20. http://dx.doi.org/10.3141/2085-02.

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Stochastic optimization has become one of the important modeling approaches in transportation network analysis. For example, for traffic assignment problems based on stochastic simulation, it is necessary to use a mathematical algorithm that iteratively seeks out the optimal, the suboptimal solution, or both, because an analytical (closed-form) objective function is not available. Therefore, efficient stochastic approximation algorithms that can find optimal or suboptimal solutions to these problems are needed. The method of successive averages (MSA), a well-known algorithm, is used to solve b

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Kováč, Szabolcs, German Micha’čonok, Igor Halenár, and Pavel Važan. "Comparison of Heat Demand Prediction Using Wavelet Analysis and Neural Network for a District Heating Network." Energies 14, no. 6 (2021): 1545. http://dx.doi.org/10.3390/en14061545.

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Short-Term Load Prediction (STLP) is an important part of energy planning. STLP is based on the analysis of historical data such as outdoor temperature, heat load, heat consumer configuration, and the seasons. This research aims to forecast heat consumption during the winter heating season. By preprocessing and analyzing the data, we can determine the patterns in the data. The results of the data analysis make it possible to form learning algorithms for an artificial neural network (ANN). The biggest disadvantage of an ANN is the lack of precise guidelines for architectural design. Another dis

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Kocaoglu, Yasemin, Emre Cakmak, Batuhan Kocaoglu, and Alev Taskin Gumus. "A Novel Approach for Optimizing the Supply Chain: A Heuristic-Based Hybrid Algorithm." Mathematical Problems in Engineering 2020 (February 27, 2020): 1–24. http://dx.doi.org/10.1155/2020/3943798.

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Managing the distribution of goods is a vital operation for many companies. A successful distribution system requires an effective distribution strategy selection and optimum route planning at the right time and minimum cost. Furthermore, customer’s demand and location can vary from order to order. In this situation, a mixed delivery system is a good solution for it and allows the use of different strategies together to decrease delivery costs. Although the “distribution strategy selection” is a critical issue for companies, there are only a few studies that focus on the mixed delivery network

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Silva, Alex Takeo Yasumura Lima, Fernando Das Graças Braga da Silva, André Carlos da Silva, José Antonio Tosta dos Reis, Claudio Lindemberg de Freitas, and Victor Eduardo de Mello Valério. "Proposal of optimal operation strategy applied to water distribution network with statistical approach." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 15, no. 2 (2020): 1. http://dx.doi.org/10.4136/ambi-agua.2455.

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Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using

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MA, WEI-MIN, SHAO-HUA TANG, and KE WANG. "COMPETITIVE ANALYSIS FOR THE MOST RELIABLE PATH PROBLEM WITH ONLINE AND FUZZY UNCERTAINTIES." International Journal of Pattern Recognition and Artificial Intelligence 22, no. 01 (2008): 195–206. http://dx.doi.org/10.1142/s0218001408006156.

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Based on some results of the fuzzy network computation and competitive analysis, the Online Fuzzy Most Reliable Path Problem (OFRP), which is one of the most important problems in network optimization with uncertainty, has been originally proposed by our team. In this paper, the preliminaries about fuzzy and the most reliable path and competitive analysis are given first. Following that, the mathematical model of OFRP, in which two kinds of uncertainties, namely online and fuzzy, are combined to be considered at the same time, is established. Then some online fuzzy algorithms are developed to

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Lin, Liu, Li, et al. "Optimal Placement of Multiple Feeder Terminal Units Using Intelligent Algorithms." Applied Sciences 10, no. 1 (2019): 299. http://dx.doi.org/10.3390/app10010299.

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In order to solve the placement problem of three kinds of feeder terminal units (FTU) in the distribution network, this paper proposes a novel mathematical model. The model considers economic cost and electricity supply reliability from the perspective of life cycle cost. The reliability algorithm in this model is established for the distribution network configured with centralized feeder automation. Different evaluation indices of reliability and the importance of several kinds of customers are also considered in this model. Aiming at the reliability evaluation in this model, this paper puts

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Kovács, Benedek, M. Szalay, and S. Imre. "Modelling and Quantitative Analysis of LTRACK–A Novel Mobility Management Algorithm." Mobile Information Systems 2, no. 1 (2006): 21–50. http://dx.doi.org/10.1155/2006/218736.

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This paper discusses the improvements and parameter optimization issues of LTRACK, a recently proposed mobility management algorithm. Mathematical modelling of the algorithm and the behavior of the Mobile Node (MN) are used to optimize the parameters of LTRACK. A numerical method is given to determine the optimal values of the parameters. Markov chains are used to model both the base algorithm and the so-called loop removal effect. An extended qualitative and quantitative analysis is carried out to compare LTRACK to existing handover mechanisms such as MIP, Hierarchical Mobile IP (HMIP), Dynam

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Zhang, Zaifang, Darao Xu, Egon Ostrosi, and Hui Cheng. "Optimization of the Product–Service System Configuration Based on a Multilayer Network." Sustainability 12, no. 2 (2020): 746. http://dx.doi.org/10.3390/su12020746.

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Product–service systems (PSS) accelerate the transition of value creation patterns for manufacturing industries, from product design and production to the delivery of overall solution integrating products and services. Existing PSS configuration solutions provide customers with preferable product modules and service modules characterized by the module granularity. Every service module is essentially a whole service flow. However, the performance of the PSS configuration solution is greatly influenced by service details. In summary, this paper studied the configuration optimization of product-o

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Miljković, Katarina, and Milica Petrović. "Integrated process planning and scheduling in dynamic environment: The state-of-the-art." Tehnika 75, no. 6 (2020): 733–46. http://dx.doi.org/10.5937/tehnika2006733m.

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This paper gives a detailed state-of-the art in the research area o f the important function o f Intelligent Manufacturing Systems (IMS) - integrated process planning and scheduling o f manufacturing systems in dynamic environment (DIPPS). Referring to this, description o f the DIPPS problem is given, the criteria on the basis o f which the optimal rescheduling plan are formulated and considered, the adopted assumptions are defined and the mathematical model o f this problem is presented. Furthermore, the disturbances that occur in manufacturing systems are considered in detail: (i) machine br

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Devarapalli, Ramesh, and Biplab Bhattacharyya. "A novel hybrid AGWO-PSO algorithm in mitigation of power network oscillations with STATCOM." Numerical Algebra, Control & Optimization 11, no. 4 (2021): 579. http://dx.doi.org/10.3934/naco.2020057.

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<p style='text-indent:20px;'>The assimilation of flexible AC transmission (FACTS) controllers to the existing power network outweigh the numerous alternatives in enhancing the damping behavior for the inter-area /intra-area system oscillations of a power network. This paper provides a rigorous analysis in damping of oscillations in a power network. It utilizes a shunt connected voltage source converter (VSC) based FACTS device to enhance the system operating characteristics. A comprehensive system mathematical modelling has been developed for demonstrating the system behavior under diffe

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Morozov, A. Yu, D. L. Reviznikov, and K. K. Abgaryan. "Issues of implementing neural network algorithms on memristor crossbars." Izvestiya Vysshikh Uchebnykh Zavedenii. Materialy Elektronnoi Tekhniki = Materials of Electronics Engineering 22, no. 4 (2020): 272–78. http://dx.doi.org/10.17073/1609-3577-2019-4-272-278.

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The property of natural parallelization of matrix-vector operations inherent in memristor crossbars creates opportunities for their effective use in neural network computing. Analog calculations are orders of magnitude faster in comparison to calculations on the central processor and on graphics accelerators. Besides, mathematical operations energy costs are significantly lower. The essential feature of analog computing is its low accuracy. In this regard, studying the dependence of neural network quality on the accuracy of setting its weights is relevant. The paper considers two convolutional

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Bakievna Khuzyatova, Lyalya, and Lenar Ajratovich Galiullin. "Optimization of parameters of neuro-fuzzy model." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 1 (2020): 229. http://dx.doi.org/10.11591/ijeecs.v19.i1.pp229-232.

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<p>The need for increasing the efficiency of the neuron-fuzzy model in the formation of knowledge bases is being updated. The task is to develop methods and algorithms for presetting and optimizing the parameters of a fuzzy neural network. To solve difficult formalized tasks, it is necessary to develop decision support systems - expert systems based on a knowledge base. ES developers are constantly faced with the problems of “extraction” and formalization of knowledge, as well as the search for new ways to obtain it. To do this, use the extraction, acquisition and formation of knowledge.

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Tarapata, Zbigniew. "Selected Multicriteria Shortest Path Problems: An Analysis of Complexity, Models and Adaptation of Standard Algorithms." International Journal of Applied Mathematics and Computer Science 17, no. 2 (2007): 269–87. http://dx.doi.org/10.2478/v10006-007-0023-2.

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Selected Multicriteria Shortest Path Problems: An Analysis of Complexity, Models and Adaptation of Standard AlgorithmsThe paper presents selected multicriteria (multiobjective) approaches to shortest path problems. A classification of multi-objective shortest path (MOSP) problems is given. Different models of MOSP problems are discussed in detail. Methods of solving the formulated optimization problems are presented. An analysis of the complexity of the presented methods and ways of adapting of classical algorithms for solving multiobjective shortest path problems are described. A comparison o

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Fwa, T. F., W. T. Chan, and K. Z. Hoque. "Analysis of Pavement Management Activities Programming by Genetic Algorithms." Transportation Research Record: Journal of the Transportation Research Board 1643, no. 1 (1998): 1–6. http://dx.doi.org/10.3141/1643-01.

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The application of genetic algorithms to programming of pavement maintenance activities at the network level is demonstrated. The operational characteristics of the genetic algorithm technique and its relevance to solving the programming problem in a Pavement Management System (PMS) are discussed. The robust search capability of genetic algorithms enables them to effectively handle the highly constrained problem of pavement management activities programming, which has an extremely large solution space of astronomical scale. Examples are presented to highlight the versatility of genetic algorit

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Rudas, Imre J. "Intelligent Engineering Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 2, no. 3 (1998): 69–71. http://dx.doi.org/10.20965/jaciii.1998.p0069.

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Building intelligent systems has been one of the great challenges since the early days of human culture. From the second half of the 18th century, two revolutionary changes played the key role in technical development, hence in creating engineering and intelligent engineering systems. The industrial revolution was made possible through technical advances, and muscle power was replaced by machine power. The information revolution of our time, in turn, canbe characterized as the replacement of brain power by machine intelligence. The technique used to build engineering systems and replace muscle

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Dimitriou, Loukas, Antonios Kaltsounis, and Antony Stathopoulos. "Pareto Evolutionary Optimization of Joint Network Design and Pricing Strategies Related to Emissions in Urban Networks." International Journal of Operations Research and Information Systems 5, no. 2 (2014): 56–85. http://dx.doi.org/10.4018/ijoris.2014040104.

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In the current social, physical, economical and environmental circumstances of scarcity, the design and management of vital lifelines like transportation systems, especially within the metropolitan context, are subject to the implementation of multiple objectives in a unified framework. Thus, one of the most important issues is the identification of optimal trade-offs among crucial objectives both from the designer's as well as from the users' perspective. In the current study a comprehensive framework for estimating optimal interrelations and dilemmas among emissions-related carbon footprint

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Parfenov, Denis I., Irina P. Bolodurina, and Vadim A. Torchin. "Development and Study of Algorithms for the Formation of Rules for Network Security Nodes in the Multi-Cloud Platform." Modeling and Analysis of Information Systems 26, no. 1 (2019): 90–100. http://dx.doi.org/10.18255/1818-1015-2019-1-90-100.

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As part of the study, existing solutions aimed at ensuring the security of the network perimeter of the multi-cloud platform were considered. It is established that the most acute problem is the effective formation of rules on firewalls. Existing approaches do not allow optimizing the list of rules on nodes that control access to the network. The aim of the study is to increase the effectiveness of firewall tools by conflict-free optimization of security rules and the use of a neural network approach in software-defined networks. The proposed solution is based on the sharing of intelligent mat

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Bakievna Khuzyatova, Lyalya, and Lenar Ajratovich Galiullin. "Optimization of parameters of neuro-fuzzy model." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (2020): 1206. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1206-1209.

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<p>The questions and problems of the formation of knowledge bases of intelligent man-machine decision support systems are considered. The neuron-fuzzy model used in the work is described. The need for increasing the efficiency of the neuron-fuzzy model in the formation of knowledge bases is being updated. The task is to develop methods and algorithms for presetting and optimizing the parameters of a fuzzy neural network. To solve difficult formalized tasks, it is necessary to develop decision support systems - expert systems based on a knowledge base. ES developers are constantly faced w

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Pechenkin, Vitaly, Mikhail Korolev, and Lyubomir Dimitrov. "Applied Aspects of Ranking Algorithms for Oriented Weighted Graphs (on The Example of Social Network Graphs)." SPIIRAS Proceedings 6, no. 61 (2018): 94–118. http://dx.doi.org/10.15622/sp.61.4.

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The article deals with the applied aspects of the preliminary vertices ranking for oriented weighted graph. In this paper, the authors observed the widespread use of this technique in developing heuristic discrete optimization algorithms. The ranking problem is directly related to the problem of social networks centrality and large real world data sets but as shown in the article ranking is explicitly or implicitly used in the development of algorithms as the initial stage of obtaining a solution for solving applied problems. Examples of such ranking application are given. The examples demonst

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Posmetev, Valeriy, Vadim Nikonov, and Viktor Posmetev. "MULTI-FACTOR OPTIMIZATION OF PARAMETERS OF THE RESEARCHED ENERGY SAVING SYSTEMS APPLIED IN TIMBER ROAD TRANSPORT." Forestry Engineering Journal 10, no. 3 (2020): 104–23. http://dx.doi.org/10.34220/issn.2222-7962/2020.3/11.

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A promising direction has been substantiated that increases the efficiency of timber road transport during timber hauling, based on the development and use of various recuperative mechanisms in its design. The analysis of foreign literature has been carried out and the authors' developments and the obtained research results in this area are described. Parametric optimization of eight types of investigated recuperative energy-saving systems has been carried out on the basis of mathematical modeling. A diagram of options for optimizing the design parameters of energy-saving systems is presented,

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