Metaheuristics for the online printing shop scheduling problem

被引:19
作者
Lunardi, Willian T. [1 ]
Birgin, Ernesto G. [2 ]
Ronconi, Debora P. [3 ]
Voos, Holger [1 ]
机构
[1] Univ Luxembourg, 29 John F Kennedy, L-1855 Luxembourg, Luxembourg
[2] Univ Sao Paulo, Inst Math & Stat, Dept Comp Sci, Rua Matao 1010,Cidade Univ, BR-05508090 Sao Paulo, SP, Brazil
[3] Univ Sao Paulo, Polytech Sch, Dept Prod Engn, Av Prof Luciano Gualberto 1380,Cidade Univ, BR-05508090 Sao Paulo, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Metaheuristics; Local search; Flexible job shop scheduling; Sequencing flexibility; Online printing shop scheduling; FLEXIBLE JOB-SHOP; DIFFERENTIAL EVOLUTION; TABU SEARCH; GENETIC ALGORITHM; OPTIMIZATION;
D O I
10.1016/j.ejor.2020.12.021
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In this work, the online printing shop scheduling problem is considered. This challenging real-world scheduling problem, that emerged in the present-day printing industry, corresponds to a flexible job shop scheduling problem with sequencing flexibility; and it presents several complicating requirements such as resumable operations, periods of unavailability of the machines, sequence-dependent setup times, partial overlapping between operations with precedence constraints, and fixed operations, among others. A local search strategy and metaheuristics are proposed and evaluated. Based on a common representation scheme, trajectory and populational metaheuristics are considered. Extensive numerical experiments on large-sized instances show that the proposed methods are suitable for solving practical instances of the problem; and that they outperform a half-heuristic-half-exact off-the-shelf solver by a large extent. In addition, numerical experiments on classical instances of the flexible job shop scheduling problem show that the proposed methods are also competitive when applied to this particular case. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:419 / 441
页数:23
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