POPMUSIC for a real-world large-scale vehicle routing problem with time windows

被引:23
作者
Ostertag, A.
Doerner, K. F. [1 ]
Hartl, R. F.
Taillard, E. D. [2 ]
Waelti, P. [2 ]
机构
[1] Univ Vienna, Dept Business Adm, A-1210 Vienna, Austria
[2] Univ Appl Sci, Yverdon, Switzerland
基金
奥地利科学基金会;
关键词
vehicle routing; heuristics; problem decomposition; VARIABLE NEIGHBORHOOD SEARCH; GUIDED EVOLUTION STRATEGIES; ALGORITHM;
D O I
10.1057/palgrave.jors.2602633
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper presents a heuristic approach based on the POPMUSIC framework for a large-scale Multi Depot Vehicle Routing Problem with Time Windows derived from real-world data. POPMUSIC is a very powerful tool for tackling large problem instances. A Memetic Algorithm is used as an optimizer in the POPMUSIC framework. It is shown that a population-based search combined with decomposition strategies is a very efficient and flexible tool to tackle real-world problems with regards to solution quality as well as runtime. Journal of the Operational Research Society ( 2009) 60, 934-943. doi:10.1057/palgrave.jors.2602633
引用
收藏
页码:934 / 943
页数:10
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