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

[ X ]

Tarih

2021

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

Künye