Adaptive GVNS Heuristics for Solving the Pollution Location Inventory Routing Problem

被引：1
|
作者：
Karakostas, Panagiotis [1 ]
Sifaleras, Angelo [2 ]
Georgiadis, Michael C. [1 ]
机构：
[1] Aristotle Univ Thessaloniki, Dept Chem Engn, Univ Campus, Thessaloniki 54124, Greece
[2] Univ Macedonia, Sch Informat Sci, Dept Appl Informat, 156 Egnatia Str, Thessaloniki 54636, Greece
来源：
LEARNING AND INTELLIGENT OPTIMIZATION, LION | 2020年 / 11968卷
关键词：
Adaptive General Variable Neighborhood Search; Intelligent optimization methods; Pollution Location Inventory Routing Problem; Green logistics; VARIABLE NEIGHBORHOOD SEARCH;
D O I：
10.1007/978-3-030-38629-0_13
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This work proposes Adaptive General Variable Neighborhood Search metaheuristic algorithms for the efficient solution of Pollution Location Inventory Routing Problems (PLIRPs). A comparative computational study, between the proposed methods and their corresponding classic General Variable Neighborhood Search versions, illustrates the effectiveness of the intelligent mechanism used for automating the re-ordering of the local search operators in the improvement step of each optimization method. Results on 20 PLIRP benchmark instances show the efficiency of the proposed metaheuristics.
引用
收藏
页码：157 / 170
页数：14
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