DocumentCode
238620
Title
AIRP: A heuristic algorithm for solving the unrelated parallel machine scheduling problem
Author
Perdigao Cota, Luciano ; Nohra Haddad, Matheus ; Freitas Souza, Marcone Jamilson ; Nazario Coelho, Vitor
Author_Institution
Dept. of Comput. Sci., Fed. Univ. of Ouro Preto, Ouro Preto, Brazil
fYear
2014
fDate
6-11 July 2014
Firstpage
1855
Lastpage
1862
Abstract
This paper deals with the Unrelated Parallel Machine Scheduling Problem with Setup Times (UPMSPST). The objective is to minimize the makespan. In order to solve it, we propose a heuristic algorithm, based on Iterated Local Search (ILS), Variable Neighborhood Descent (VND) and Path Relinking (PR). In this algorithm, named AIRP, an initial solution is constructed using the Adaptive Shortest Processing Time method. This solution is refined by the ILS, having an adaptation of the VND as local search method. The PR method is applied as a strategy of intensification and diversification during the search. The algorithm was tested in instances of the literature envolving up to 150 jobs and 20 machines. The computational experiments show that the proposed algorithm outperforms an algorithm from the literature, both in terms of quality and variability of the final solution. In addition, the algorithm established new best solutions for more than 80,5% of the test problems in average.
Keywords
iterative methods; minimisation; scheduling; search problems; AIRP; ILS; PR; UPMSPST; VND; adaptive shortest processing time method; diversification strategy; heuristic algorithm; intensification strategy; iterated local search; local search method; makespan minimization; path relinking; solution quality; solution variability; unrelated parallel machine scheduling problem-with-setup times; variable neighborhood descent; Educational institutions; Heuristic algorithms; Job shop scheduling; Parallel machines; Processor scheduling; Schedules; Space exploration;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6626-4
Type
conf
DOI
10.1109/CEC.2014.6900245
Filename
6900245
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