首页    期刊浏览 2024年11月27日 星期三
登录注册

文章基本信息

  • 标题:An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem
  • 本地全文:下载
  • 作者:Weizhen Rao ; Feng Liu ; Shengbin Wang
  • 期刊名称:Applied Computational Intelligence and Soft Computing
  • 印刷版ISSN:1687-9724
  • 电子版ISSN:1687-9732
  • 出版年度:2016
  • 卷号:2016
  • DOI:10.1155/2016/3713918
  • 出版社:Hindawi Publishing Corporation
  • 摘要:The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.
国家哲学社会科学文献中心版权所有