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24th Wireless and Optical Communication Conference (WOCC)

作者： Wang, Chia-Hung Lee, Chia-Jung Chung, Wei-Ho Wu, Mu-En Fujian Univ Technol Coll Informat Sci & Engn Fuzhou Fujian Province Peoples R China Acad Sinica Res Ctr Informat Technol Innovat Taipei 115 Taiwan Soochow Univ Dept Math Taipei Taiwan

ISBN: (纸本)9781479988549

In this paper, we study an extension of atomic routing games for multi-class communication networks with quality of service requirements, which can be formulated as a network management scheme. Atomic routing games are noncooperative games with multiple selfish players, where each player has to choose a path in a given graph to route his traffic, and then pays the corresponding cost. We develop a mixed-integer nonlinear programming model for the network management scheme in this class-based communication network. The analysis of this work offers appropriate resource allocation and a routing database identifying suitable end-to-end paths upon each connection request.

关键词： atomic routing game end-to-end routing band-width allocation mixed-integer nonlinear programming

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Planning a Capacitated Road Network with Flexible Travel Times: A Genetic Algorithm

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Journal of Mathematical Modelling and Algorithms in Operations Research 2015年第4期14卷 425-451页

作者： Shiripour, Saber Mahdavi-Amiri, Nezam Mahdavi, Iraj Department of Industrial Engineering Mazandaran University of Science & Technology Babol Iran Faculty of Mathematical Sciences Sharif University of Technology Tehran Iran

We are concerned with a capacitated location-multi allocation-routing problem in a road network with flexible travel times. It is assumed that all links are two-way and capacities of the server nodes and arcs for accepting of population are limited. The aim of our work is to find numbers and locations of server nodes, allocation of the existing population in existing demand nodes on the network to the servers and the allocation of existing population in each node to different routes to determine the decided server for each member so that total transportation time is minimized. Here, two basic concepts are considered: multi allocation and flexible travel times. The concept of multi allocation arises from the possibility of allocating the existing population in a demand node to more than one server node. Also, flexible travel times concentrate on impact of traveling population on the times of links simultaneously, that is, depending on how the population is distributed on the network, the travel times on links may be increased. So, to have the least increase in the time of each link, it is necessary to decide upon the distribution of population in the network. We formulate the proposed problem as a mixed-integer nonlinear programming model and then present a genetic algorithm (GA) for solving large problems Finally, we make two sets of numerical experiments and analyze the obtained results by LINGO solver and GA. Numerical results show the proposed GA to be highly efficient. © 2015, Springer Science+Business Media Dordrecht.

关键词： Capacitated location-multi allocation-routing problem Flexible travel times Genetic algorithm mixed-integer nonlinear programming

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Schedule Design for Liner Shipping Based on Wave Optimization 5

Schedule Design for Liner Shipping Based on Wave Optimizatio...

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5th International Conference on Transportation Engineering, ICTE 2015

作者： Xing, Jiangbo Zhong, Ming Transportation Management College Dalian Maritime University Dalian China

ISBN: (数字)9780784479384

ISBN: (纸本)9780784479384

This paper focuses on the schedule design problem for liner shipping to hedge against uncertainties. As a complement of Robust Optimization, a new optimization method-Wave Optimization (WO) is proposed, which is more suitable for socioeconomic systems. Then a mixed-integer nonlinear programming model based on WO is presented to solve the vessel schedule design problem. A real-life case study is investigated and proves that the proposed model could be solved effectively and efficiently for the realistic scale problem. © ASCE.

关键词： Liner shipping Schedule design Wave optimization mixed-integer nonlinear programming Liner shipping mixed integer linear programming design problems optimization method

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Solving reliability redundancy allocation problems with orthogonal simplified swarm optimization

Solving reliability redundancy allocation problems with orth...

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International Joint Conference on Neural Networks

作者： Wei-Chang Yeh Vera Yuk Ying Chung Yun-Zhi Jiang Xiangjian He Department of Industrial Engineering and Engineering Managemen National Tsing Hua University Hsinchu 300 Taiwan School of Information Technology University of Sydney NSW 2006 Australia School of Software Jiangxi Agricultural University Nanchang China 330045 School of Software Engineering South China University of Technology Guangzhou China 510006 Computer Vision and Recognition Laboratory Research Centre for Innovation in IT Services and Applications (iNEXT) University of Technology Sydney (UTS) PO Box 123 Broadway NSW 2007 Australia

ISBN: (纸本)9781479919611

This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series system, the series-parallel system, the complex (bridge) system, and the overspeed protection of gas turbine system. For several decades, the RRAP has been one of the most well known techniques. The maximization of system reliability, the number of redundant components, and the reliability of corresponding components in each subsystem have to be decided simultaneously with nonlinear constraints, acting as one difficulty for the use of the RRAP. In other words, the objective function of the RRAP is the mixed-integer programming problem with the nonlinear constraints. The RRAP is of the class of NP-hard. Hence, in this paper, the SSO algorithm is proposed to solve the RRAP and improve computation efficiency for these NP-hard problems. There are four RRAP problems used to illustrate the applicability and the effectiveness of the SSO. The experimental results are compared with previously developed algorithms in literature. Moreover, the maximum-possible-improvement (MPI) is used to measure the amount of improvement of the solution found by the SSO to the previous solutions. According to the results, the system reliabilities obtained by the proposed SSO for the four RRAP problems are as well as or better than the previously best-known solutions.

关键词： Reliability Redundancy allocation problem RRAP Simplified Swarm Optimization algorithm SSO mixed-integer nonlinear programming

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mixed-integer programming for a new bus-lane reservation problem

Mixed-integer programming for a new bus-lane reservation pro...

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International IEEE Conference on Intelligent Transportation Systems

作者： Peng Wu Feng Chu Ada Che Sch. of Manage. Northwestern Polytech. Univ. Xi'an China

ISBN: (纸本)9781467365970

In this paper, we investigate a new bus-lane reservation problem in transportation network, which aims to optimally decide which lanes to be reserved for the exclusive use of buses and design bus transit paths for bus lines to achieve time-efficient bus transit with stop time window constraints. However, an exclusive bus-lane may cause negative impact on non-bus vehicles running on its adjacent non-reserved lanes as it reduces their available lanes. The objective of the problem is to minimize the total negative impact caused by reserved lanes. To address this problem, we first formulate a mixed-integer non-linear program and its complexity is proved to be NP-hard. Then, the nonlinear model is equivalently transformed into an linear one. Furthermore, properties of the problem are analyzed to reduce the search space for optimal solutions and tighten the proposed linear model. Finally, it is solved using commercial optimization software CPLEX. Computational results on randomly generated instances show the effectiveness of the proposed approach.

关键词： computational complexity integer programming nonlinear programming public transport NP-hard complexity bus-lane reservation problem mixed-integer nonlinear programming transportation network Complexity theory Computational modeling Mathematical model Optimization Roads Vehicles

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Water Resources Planning and Management by Use of Generalized Benders Decomposition Method to Solve Large-scale MINLP Problems

Water Resources Planning and Management by Use of Generalize...

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2015水资源与环境国际会议

作者： André A.Keller Lille 1 University – Science and Technology

Water resources systems(WRS)models involve a large number of continuous and integer *** quality management problems also require the consideration of uncertainties related to the variability of flow streams and *** dynamics are primarily *** characteristic features suggest the use of(stochastic)mixed-integer programming models,as well the use of sensibility analysis and ***,high dimensional real-world models and combinatorial alternatives require adequate tools for large-scale optimization *** techniques consist of decomposition methods such as the generalized Benders decomposition(GBD)and the branch-and-bound enumerative *** contribution introduces the subject of modeling WRSs by use of GBD and branch-and-bound algorithms with numerical applications.

关键词： mixed-integer nonlinear programming Large-Scale Optimization Methods Generalized Benders Decomposition Algorithm Water Resource System Groundwater Management Water Quality Management

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Undercover: a primal MINLP heuristic exploring a largest sub-MIP

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MATHEMATICAL programming 2014年第1-2期144卷 315-346页

作者： Berthold, Timo Gleixner, Ambros M. Zuse Inst Berlin Dept Optimizat D-14195 Berlin Germany

We present Undercover, a primal heuristic for nonconvex mixed-integer nonlinear programs (MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We solve a vertex covering problem to identify a smallest set of variables to fix, a so-called cover, such that each constraint is linearized. Subsequently, these variables are fixed to values obtained from a reference point, e.g., an optimal solution of a linear relaxation. Each feasible solution of the sub-MIP corresponds to a feasible solution of the original problem. We apply domain propagation to try to avoid infeasibilities, and conflict analysis to learn additional constraints from infeasibilities that are nonetheless encountered. We present computational results on a test set of mixed-integer quadratically constrained programs (MIQCPs) and MINLPs. It turns out that the majority of these instances allows for small covers. Although general in nature, we show that the heuristic is most successful on MIQCPs. It nicely complements existing root-node heuristics in different state-of-the-art solvers and helps to significantly improve the overall performance of the MINLP solver SCIP.

关键词： Primal heuristic mixed-integer nonlinear programming Large neighborhood search mixed-integer quadratically constrained programming Nonconvex optimization

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Design and analysis of demand-adapted railway timetables

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JOURNAL OF ADVANCED TRANSPORTATION 2014年第2期48卷 119-137页

作者： Canca, David Barrena, Eva Algaba, Encarnacion Zarzo, Alejandro Univ Seville Escuela Tecn Super Ingn Seville 41092 Spain Univ Politecn Madrid ETSII Escuela Tecn Super Ingn Ind E-28006 Madrid Spain

Railway scheduling and timetabling are common stages in the classical hierarchical railway planning process and they perhaps represent the step with major influence on user's perception about quality of service. This aspect, in conjunction with their contribution to service profitability, makes them a widely studied topic in the literature, where, nowadays, many efforts are focused on improving the solving methods of the corresponding optimization problems. However, literature about models considering detailed descriptions of passenger demand is sparse. This paper tackles the problem of timetable determination by means of building and solving a nonlinear integer programming model that fits the arrival and departure train times to a dynamic behavior of demand. The optimization model results are then used for computing several measures to characterize the quality of the obtained timetables considering jointly both user and company points of view. Some aspects are discussed, including the influence of train capacity and the validity of Random Incidence Theorem. An application to the C5 line of Madrid rapid transit system is presented. Different measures are analyzed in order to improve the insight into the proposed model and analyze in advance the influence of different objectives on the resulting timetable. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： train timetabling quality of service variable demand mixed-integer nonlinear programming

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Optimization for design and operation of natural gas transmission networks

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APPLIED ENERGY 2014年 133卷 56-69页

作者： Uester, Halit Dilaveroglu, Sebnem Texas A&M Univ Dept Ind & Syst Engn College Stn TX 77843 USA BOTAS Petr Pipeline Corp Ankara Turkey

We consider the problem of designing a new natural gas transmission network or expanding an existing network while minimizing the total investment and operating costs. We develop an integrated large-scale mixed-integer nonlinear optimization model to determine pipelines in the network, compressor stations and their capacities, timings of these installations in a multi-period planning horizon, and natural gas purchase and steady-state flow decisions for each period in the network. The model is solvable using state-of-the-art solution methodologies available online. Employing our modeling and the solution methodology for its solution, we conduct computational studies on various test instances generated using realistic network structure and data based on the natural gas network in Turkey as well as data from literature. Our analysis provides insights into sensitivity of network configuration and operations to the number of periods within the planning horizon and cost parameters as well as into strategic decision making for design and expansion of natural gas networks. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Natural gas Network design Multi-period planning mixed-integer nonlinear programming

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Linearization-based algorithms for mixed-integer nonlinear programs with convex continuous relaxation

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第2-3期59卷 343-365页

作者： Hamzeei, Mahdi Luedtke, James Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

We present two linearization-based algorithms for mixed-integer nonlinear programs (MINLPs) having a convex continuous relaxation. The key feature of these algorithms is that, in contrast to most existing linearization-based algorithms for convex MINLPs, they do not require the continuous relaxation to be defined by convex nonlinear functions. For example, these algorithms can solve to global optimality MINLPs with constraints defined by quasiconvex functions. The first algorithm is a slightly modified version of the LP/NLP-based branch-and-bouund algorithm of Quesada and Grossmann, and is closely related to an algorithm recently proposed by Bonami et al. (Math Program 119:331-352, 2009). The second algorithm is a hybrid between this algorithm and nonlinear programming based branch-and-bound. Computational experiments indicate that the modified LP/NLP-BB method has comparable performance to LP/NLP-BB on instances defined by convex functions. Thus, this algorithm has the potential to solve a wider class of MINLP instances without sacrificing performance.

关键词： mixed-integer nonlinear programming Quasiconvex function Outer approximation

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