.png){kind=icon}
返回
Stochastic multi-objective models for network design problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2009.06.048.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Transportation network design problem (NDP) is inherently multi-objective in nature, because it involves a number of stakeholders with different needs. In addition, the decision-making process sometimes has to be made under uncertainty where certain inputs are not known exactly. In this paper, we develop three stochastic multi-objective models for designing transportation network under demand uncertainty. These three stochastic multi-objective NDP models are formulated as the expected value multi-objective programming (EVMOP) model, chance constrained multi-objective programming (CCMOP) model, and dependent chance multi-objective programming (DCMOP) model in a bi-level programming framework using different criteria to hedge against demand uncertainty. To solve these stochastic multi-objective NDP models. we develop a solution approach that explicitly optimizes all objectives under demand uncertainty by simultaneously generating a family of optimal solutions known as the Pareto optimal solution set. Numerical examples are also presented to illustrate the concept of the three stochastic multi-objective NDP models as well as the effectiveness of the solution approach. Published by Elsevier Ltd.
Keyword:
User equilibrium
Traffic assignment
Network design
Bi-level program
Stochastic program
Multi-objective
Genetic algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
分享收藏
Characterization of the products obtained from the reactions of Zircaloy-4 with an acid mixture of concentrated HNO3and dilute HF with the aim of understanding pickle salts of zirconium alloys.png)
RSC Adv.
RSC Adv.IF0
PREAI
分享收藏Effects of regulation on highway pricing and capacity choice of a build-operate-transfer scheme
PREAI
分享收藏
查看更多内容