A Hybrid Monte Carlo Local Branching Algorithm for the Single Vehicle Routing Problem with Stochastic Demands

被引：52
|
作者：
Rei, Walter [1 ,2 ]
Gendreau, Michel [2 ,3 ]
Soriano, Patrick [2 ,4 ]
机构：
[1] Univ Quebec, Dept Management & Technol, Ecole Sci Gest, Montreal, PQ H3C 3P8, Canada
[2] CIRRELT, Montreal, PQ H3C 3J7, Canada
[3] Ecole Polytech, Dept Math & Genie Ind, Montreal, PQ H3C 3J7, Canada
[4] HEC Montreal, Serv Methodes Quantitat Gest, Montreal, PQ H3T 2A7, Canada
来源：
TRANSPORTATION SCIENCE | 2010年 / 44卷 / 01期
基金：
加拿大自然科学与工程研究理事会;
关键词：
local branching; Monte Carlo sampling; stochastic vehicle routing problems; AVERAGE APPROXIMATION METHOD;
D O I：
10.1287/trsc.1090.0295
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
We present a new algorithm that uses both local branching and Monte Carlo sampling in a multidescent search strategy for solving 0-1 integer stochastic programming problems. This procedure is applied to the single-vehicle routing problem with stochastic demands. Computational results show the effectiveness of this new approach to solving hard instances of the problem.
引用
收藏
页码：136 / 146
页数：11
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