A Genetic Algorithm Approach to Parallel Machine Scheduling Problems Under Effects of Position-Dependent Learning and Linear Deterioration: Genetic Algorithm to Parallel Machine Scheduling Problems
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Igi Global
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper investigates parallel machine scheduling problems where the objectives are to minimize total completion times under effects of learning and deterioration. The investigated problem is in NP-hard class and solution time for finding optimal solution is extremely high. The authors suggested a genetic algorithm, a well-known and strong metaheuristic algorithm, for the problem and we generated some test problems with learning and deterioration effects. The proposed genetic algorithm is compared with another existing metaheuristic for the problem. Experimental results show that the proposed genetic algorithm yield good solutions in very short execution times and outperforms the existing metaheuristic for the problem.
Açıklama
Anahtar Kelimeler
Deterioration Effect, Genetic Algorithm, Learning Effect, Parallel Machine
Kaynak
International Journal of Applied Metaheuristic Computing
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
12
Sayı
3