Evolutionary tabu search for flexible due-date satisfaction in fuzzy job shop scheduling

被引:47
|
作者
Vela, Camino R. [1 ]
Afsar, Sezin [1 ]
Jose Palacios, Juan [1 ]
Gonzalez-Rodriguez, Ines [2 ]
Puente, Jorge [1 ]
机构
[1] Univ Oviedo, Dept Comp, Oviedo, Spain
[2] Univ Cantabria, Dept Math Stat & Comp, Santander, Spain
关键词
Scheduling; Fuzzy Sets; Metaheuristics; Due dates; Tabu search; TOTAL WEIGHTED TARDINESS; GENETIC ALGORITHM; PROCESSING TIME; OPTIMIZATION; CONSTRAINTS;
D O I
10.1016/j.cor.2020.104931
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We consider the job shop scheduling problem with fuzzy sets modelling uncertain durations and flexible due dates. With the goal of maximising due-date satisfaction under uncertainty, we first give a new measure of overall due-date satisfaction in this setting. Then, we define a neighbourhood structure for local search, analyse its theoretical properties and provide a neighbour-estimation procedure. Additionally, a tabu search procedure using the neighbourhood is combined with a genetic algorithm, so the resulting memetic algorithm, guided by the defined due-date satisfaction measure, is run on a set of benchmarks. The obtained results illustrate the potential of our proposal. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:16
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