Pruning and ranking the Pareto optimal set, application for the dynamic multi-objective network design problem

被引：0
|
作者：
机构：
[1] [1,Wismans, Luc J.J.
[2] 1,Brands, T.
[3] Van Berkum, Eric C.
[4] Bliemer, Michiel C.J.
来源：
Wismans, Luc J.J. | 1600年 / John Wiley and Sons Ltd, 410 Park Avenue, 15th Floor, 287 pmb, New York, NY 10022, United States卷 / 48期
关键词：
Solving the multi-objective network design problem (MONDP) resorts to a Pareto optimal set. This set can provide additional information like trade-offs between objectives for the decision making process; which is not available if the compensation principle would be chosen in advance. However; the Pareto optimal set of solutions can become large; especially if the objectives are mainly opposed. As a consequence; the Pareto optimal set may become difficult to analyze and to comprehend. In this case; pruning and ranking becomes attractive to reduce the Pareto optimal set and to rank the solutions to assist the decision maker. Because the method used; may influence the eventual decisions taken; it is important to choose a method that corresponds best with the underlying decision process and is in accordance with the qualities of the data used. We provided a review of some methods to prune and rank the Pareto optimal set to illustrate the advantages and disadvantages of these methods. The methods are applied using the outcome of solving the dynamic MONDP in which minimizing externalities of traffic are the objectives; and dynamic traffic management measures are the decision variables. For this; we solved the dynamic MONDP for a realistic network of the city Almelo in the Netherlands using the non-dominated sorting genetic algorithm II. For ranking; we propose to use a fuzzy outranking method that can take uncertainties regarding the data quality and the perception of decision makers into account; and for pruning; a method that explicitly reckons with significant trade-offs has been identified as the more suitable method to assist the decision making process. Copyright © 2012 John Wiley & Sons; Ltd;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Journal article (JA)
引用
收藏
相关论文
共 50 条
  • [1] Pruning and ranking the Pareto optimal set, application for the dynamic multi-objective network design problem
    Wismans, Luc J. J.
    Brands, T.
    Van Berkum, Eric C.
    Bliemer, Michiel C. J.
    JOURNAL OF ADVANCED TRANSPORTATION, 2014, 48 (06) : 588 - 607
  • [2] MULTI-OBJECTIVE EVOLUTION OF THE PARETO OPTIMAL SET OF NEURAL NETWORK CLASSIFIER ENSEMBLES
    Engen, Vegard
    Vincent, Jonathan
    Schierz, Amanda C.
    Phalp, Keith
    PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6, 2009, : 74 - 79
  • [3] Structural analyses of pareto optimal sets in multi-objective optimization application to window design problem using multi-objective genetic algorithm
    Suga, Kentaro
    Kato, Shinsuke
    Hiyama, Kyosuke
    Journal of Environmental Engineering, 2008, 73 (625) : 283 - 289
  • [4] Pruning Pareto optimal solutions for multi-objective portfolio asset management
    Petchrompo, Sanyapong
    Wannakrairot, Anupong
    Parlikad, Ajith Kumar
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 297 (01) : 203 - 220
  • [5] A genetic algorithm for the pareto optimal solution set of multi-objective shortest path problem
    胡仕成
    徐晓飞
    战德臣
    Journal of Harbin Institute of Technology, 2005, (06) : 721 - 726
  • [6] PARETO OPTIMAL SOLUTIONS FOR MULTI-OBJECTIVE GENERALIZED ASSIGNMENT PROBLEM
    Prakash, S.
    Sharma, M. K.
    Singh, A.
    SOUTH AFRICAN JOURNAL OF INDUSTRIAL ENGINEERING, 2010, 21 (02): : 91 - 100
  • [7] Multi-Objective Transit Route Network Design as Set Covering Problem
    Owais, Mahmoud
    Osman, Mostafa K.
    Moussa, Ghada
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (03) : 670 - 679
  • [8] Multi-objective optimization of a welding process by the estimation of the Pareto optimal set
    Torres-Trevino, Luis M.
    Reyes-Valdes, Felipe A.
    Lopez, Victor
    Praga-Alejo, Rolando
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (07) : 8045 - 8053
  • [9] A review of Pareto pruning methods for multi-objective optimization
    Petchrompo, Sanyapong
    Coit, David W.
    Brintrup, Alexandra
    Wannakrairot, Anupong
    Parlikad, Ajith Kumar
    COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 167
  • [10] Pareto Ranking Bisection Algorithm for Rapid Multi-Objective Design of Antenna Structures
    Koziel, Slawomir
    Bekasiewicz, Adrian
    Cheng, Qingsha S.
    Zhang, Qingfeng
    2017 IEEE MTT-S INTERNATIONAL CONFERENCE ON NUMERICAL ELECTROMAGNETIC AND MULTIPHYSICS MODELING AND OPTIMIZATION FOR RF, MICROWAVE, AND TERAHERTZ APPLICATIONS (NEMO), 2017, : 131 - 133
12345