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Non-identical Parallel Machine Scheduling Using Genetic Algorithm by Savaş Balin is a Computer Science article available to read on EtoBox.

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## GA) LPT a b s t r a c t Most of the scheduling problems are NP-hard. In the literature, several heuristics and dispatching rules are proposed to solve such hard combinatorial optimization problems and genetic algorithm (GA) ranks among the most preferred ones in view of its characteristics such as high adaptability, near optimization and easy realization. But, even though it is a common problem in the industry, only a small number of studies deal with non-identical parallel machines. In this paper, the authors propose a new ''crossover operator'' and a new ''optimality criterion'' in order to adapt the GA to non-identical parallel machine scheduling problem. New algorithm is tested on a numerical example by implementing it in a simulation software and computational results are compared to those obtained with LPT (Longest Processing Time) dispatching rule; results were promising. Findings show that, in addition to its high computational speed for larger scale problem, the GA proposed here fits the non-identical parallel machine scheduling problem of minimizing the maximum completion time (makespan).

Who reads Non-identical Parallel Machine Scheduling Using Genetic Algorithm?

Author

Savaş Balin

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0957-4174)

Published

2011

Language

EN

Field

Computer Science (Physical Sciences)