Application of genetic algorithm to industrial scheduling and problems of parameters evaluation
Articles
Edgaras Šakurovas
Kaunas University of Technology
Narimantas Listopadskis
Kaunas University of Technology
Published 2021-06-15
https://doi.org/10.15388/LMR.2007.24248
PDF

Keywords

scheduling problem
genetic algorithm
job shop
open shop
flow shop

How to Cite

Šakurovas, E. and Listopadskis, N. (2021) “Application of genetic algorithm to industrial scheduling and problems of parameters evaluation”, Lietuvos matematikos rinkinys, 47(spec.), pp. 479–483. doi:10.15388/LMR.2007.24248.

Abstract

Genetic algorithms are widely used in various mathematical and real world problems. They are approximate metaheuristic algorithms, commonly used for solving NP-hard problems in combinatorial optimisation. Industrial scheduling is one of the classical NP-hard problems. We analyze three classical industrial scheduling problems: job-shop, flow-shop and open-shop. Canonical genetic algorithm is applied for those problems varying its parameters. We analyze some aspects of parameters such as selecting optimal parameters of algorithm, influence on algorithm performance. Finally, three strategies of algorithm – combination of parameters and new conceptualmodel of genetic algorithm are proposed.

PDF

Downloads

Download data is not yet available.