The heterogeneous fleet vehicle routing problem with light loads and overtime: Formulation and population variable neighbourhood search with adaptive memory
作者:
Highlights:
• VNS-triggered memory extraction improves method performance up to 5.2%.
• Incorporating real life aspects could improve daily total routing cost up to 8%.
• Vehicle capacity and working time utilization could be improved by up to 12.5%.
• Real life aspects could improve fleet composition at no extra cost.
• Interesting managerial insights regarding real life routing trade-offs.
摘要
•VNS-triggered memory extraction improves method performance up to 5.2%.•Incorporating real life aspects could improve daily total routing cost up to 8%.•Vehicle capacity and working time utilization could be improved by up to 12.5%.•Real life aspects could improve fleet composition at no extra cost.•Interesting managerial insights regarding real life routing trade-offs.
论文关键词:Real life vehicle routing,Population Variable Neighbourhood Search,Adaptive Memory,MIP Formulation,Managerial Insights
论文评审过程:Received 6 February 2018, Revised 30 April 2018, Accepted 16 July 2018, Available online 18 July 2018, Version of Record 31 July 2018.
论文官网地址:https://doi.org/10.1016/j.eswa.2018.07.034