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报告题名:
An Adaptive Iterated Local Search for the Mixed Capacitated General Routing Problem
作者: Dell'Amico, Mauro; Diaz Diaz, Jose Carlos; Hasle, Geir; Iori, Manuel
出版年: 2014
发表日期: 2014
国家: 挪威
语种: 英语
英文摘要: We study the Mixed Capacitated General Routing Problem (MCGRP) in which a fleet of capacitated vehicles has to serve a set of requests by traversing a mixed weighted graph. The requests may be located on nodes, edges, and arcs. The problem has theoretical interest because it is a generalization of the Capacitated Vehicle Routing Problem (CVRP), the Capacitated Arc Routing Problem (CARP), and the General Routing Problem (GRP). It is also of great practical interest since it is often a more accurate model for real world cases than its widely studied specializations, particularly for so-called street routing applications. Examples are urban-waste collection, snow removal, and newspaper delivery. We propose a new Iterated Local Search metaheuristic for the problem that also includes vital mechanisms from Adaptive Large Neighborhood Search combined with further intensification through local search. The method utilizes selected, tailored, and novel local search and large neighborhood search operators, as well as a new local search strategy. Computational experiments show that the proposed metaheuristic is highly effective on five published benchmarks for the MCGRP. The metaheuristic yields excellent results also on seven standard CARP datasets, and good results on four well-known CVRP benchmarks.
URL: https://brage.bibsys.no/xmlui/bitstream/handle/11250/2379187/SINTEF%2bA26278.pdf?sequence=3&isAllowed=y
资源类型: 研究报告
标识符: http://119.78.100.158/handle/2HF3EXSE/28912
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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Recommended Citation:
Dell'Amico, Mauro,Diaz Diaz, Jose Carlos,Hasle, Geir,et al. An Adaptive Iterated Local Search for the Mixed Capacitated General Routing Problem. 2014-01-01.
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