A Global-local Neighborhood Search Algorithm and Tabu Search for Flexible Job Shop Scheduling Problem

被引：0

作者：

Serna N.J.E. ^{[1
]}

Seck-Tuoh-Mora J.C. ^{[1
]}

Medina-Marin J. ^{[1
]}

Hernandez-Romero N. ^{[1
]}

Barragan-Vite I. ^{[1
]}

Armenta J.R.C. ^{[1
]}

机构：

[1] AAIyA-ICBI-UAEH, Mineral de la Reforma, Hidalgo

来源：

PeerJ Computer Science | 2021年 / 7卷

关键词：

Cellular automata; Job shop scheduling; Local search; Simplified neighborhood; Tabu search;

D O I：

10.7717/PEERJ-CS.574

中图分类号：

学科分类号：

摘要：

The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called smart-cells generates and shares information that helps to optimize instances of the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms, using four benchmark sets and 101 test problems. Copyright 2021 Escamilla Serna et al.

引用

页码：1 / 32

页数：31

共 64 条

[1]

Adamatzky A., Game of life cellular automata, 1, (2010)

[2]

Ahmadi E, Zandieh M, Farrokh M, Emami SM., A multi objective optimization approach for flexible job shop scheduling problem under random machine breakdown by evolutionary algorithms, Computers & Operations Research, 73, 2, pp. 56-66, (2016)

[3]

Amiri M, Zandieh M, Yazdani M, Bagheri A., A variable neighbourhood search algorithm for the flexible job-shop scheduling problem, International Journal of Production Research, 48, 19, pp. 5671-5689, (2010)

[4]

An Y, Chen X, Li Y, Han Y, Zhang J, Shi H., An improved non-dominated sorting biogeography-based optimization algorithm for the (hybrid) multi-objective flexible job-shop scheduling problem, Applied Soft Computing, 99, C, (2021)

[5]

Baykasoglu A, Madenoglu FS, Hamzaday A., Greedy randomized adaptive search for dynamic flexible job-shop scheduling, Journal of Manufacturing Systems, 56, pp. 425-451, (2020)

[6]

Bharti P, Jain S., Hybrid frameworks for flexible job shop scheduling, The International Journal of Advanced Manufacturing Technology, 108, 5–6, pp. 1563-1585, (2020)

[7]

Bilan SM, Bilan MM, Motornyuk RL., New methods and paradigms for modeling dynamic processes based on cellular automata, (2020)

[8]

Blazewicz J, Domschke W, Pesch E., The job shop scheduling problem: conventional and new solution techniques, European Journal of Operational Research, 93, 1, pp. 1-33, (1996)

[9]

Brandimarte P., Routing and scheduling in a flexible job shop by tabu search, Annals of Operations research, 41, 3, pp. 157-183, (1993)

[10]

Brucker P, Schlie R., Job-shop scheduling with multi-purpose machines, Computing, 45, 4, pp. 369-375, (1990)

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