首页    期刊浏览 2024年12月12日 星期四
登录注册

文章基本信息

  • 标题:Solving a bi-objective vehicle routing problem under uncertainty by a revised multi-choice goal programming approach
  • 本地全文:下载
  • 作者:Yousefi, H. ; Yousefi, H. ; Tavakkoli-Moghaddam, R.
  • 期刊名称:International Journal of Industrial Engineering Computations
  • 印刷版ISSN:1923-2926
  • 电子版ISSN:1923-2934
  • 出版年度:2017
  • 卷号:8
  • 期号:3
  • 页码:283-302
  • DOI:10.5267/j.ijiec.2017.1.003
  • 语种:English
  • 出版社:Growing Science Publishing Company
  • 摘要:A vehicle routing problem with time windows (VRPTW) is an important problem with many real applications in a transportation problem. The optimum set of routes with the minimum distance and vehicles used is determined to deliver goods from a central depot, using a vehicle with capacity constraint. In the real cases, there are other objective functions that should be considered. This paper considers not only the minimum distance and the number of vehicles used as the objective function, the customer’s satisfaction with the priority of customers is also considered. Additionally, it presents a new model for a bi-objective VRPTW solved by a revised multi-choice goal programming approach, in which the decision maker determines optimistic aspiration levels for each objective function. Two meta-heuristic methods, namely simulated annealing (SA) and genetic algorithm (GA), are proposed to solve large-sized problems. Moreover, the experimental design is used to tune the parameters of the proposed algorithms. The presented model is verified by a real-world case study and a number of test problems. The computational results verify the efficiency of the proposed SA and GA.
  • 关键词:Vehicle routing problem; Multi-choice goal programming; Customer priority; Customer satisfaction
国家哲学社会科学文献中心版权所有