Modeling and solving the non-smooth arc routing problem with realistic soft constraints

被引:11
|
作者
de Armas, Jesica [1 ,2 ]
Ferrer, Albert [3 ]
Juan, Angel A. [4 ]
Lalla-Ruiz, Eduardo [5 ]
机构
[1] Univ Pompeu Fabra, Dept Econ & Business, Barcelona, Spain
[2] Barcelona GSE, Barcelona, Spain
[3] Tech Univ Catalonia, Dept Appl Math, Barcelona, Spain
[4] Open Univ Catalonia, IN3, Dept Comp Sci, Castelldefels, Spain
[5] Univ Hamburg, Inst Informat Syst, Hamburg, Germany
关键词
Arc routing problem; Soft constraints; Non-smooth optimization; Biased-randomization; Metaheuristics; PARTICLE SWARM OPTIMIZATION; TABU SEARCH ALGORITHM; ITERATED LOCAL SEARCH; DISPATCH;
D O I
10.1016/j.eswa.2018.01.020
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper considers the non-smooth arc routing problem (NS-ARP) with soft constraints in order to capture in more perceptive way realistic constraints violations arising in transportation and logistics. To appropriately solve this problem, a biased-randomized procedure with iterated local search (BRILS) and a mathematical model for this ARP variant is proposed. An extensive computational study is conducted on rich and diverse problem instances. The results highlight the competitiveness of BRILS in terms of quality and time, where it provides high-quality solutions within reasonable computational times. In the context of real-world environments, the performance exhibited by BRILS motivates its incorporation in intelligent and integrative systems where frequent and fast solutions are required. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:205 / 220
页数:16
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