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