Authors:
Marcelo Ferreira Rego
1
and
Marcone Jamilson Freitas Souza
2
Affiliations:
1
Universidade Federal de Ouro Preto (UFOP), Programa de Pós-Graduaç ão em Ciência da Computaç ão, 35.400-000, Ouro Preto, Minas Gerais, Brazil, Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM), 39.100-000, Diamantina and Brazil
;
2
Universidade Federal de Ouro Preto (UFOP), Programa de Pós-Graduaç ão em Ciência da Computaç ão, 35.400-000, Ouro Preto, Minas Gerais and Brazil
Keyword(s):
Unrelated Parallel Machine Scheduling, Makespan, VNS, Metaheuristic, Mathematical Programming.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
;
Operational Research
;
Scheduling and Planning
Abstract:
This work addresses the Unrelated Parallel Machine Scheduling Problem in which machine and job sequence-dependent setup time are considered. The objective is to minimize the makespan. For solving it, a Smart General Variable Neighborhood Search algorithm is proposed. It explores the solution space through five strategies: swap of jobs in the same machine, insertion of job in the same machine, swap of jobs between machines, insertion of jobs to different machines and an application of a Mixed Integer Linear Programming formulation to obtain optimum scheduling on each machine. The first four strategies are used as shaking mechanism, while the last three are applied as local search through the Variable Neighborhood Descent method. The proposed algorithm was tested in a set of 810 instances available in the literature and compared to three state-of-the-art algorithms. Although the SGVNS algorithm did not statistically outperform them in these instances, it was able to outperform them in
79 instances.
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