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

被引：46

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

来源：

COMPUTERS & OPERATIONS RESEARCH | 2020年 / 119卷

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

页数：16

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