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Three genetic algorithm approaches to parallel machine scheduling and comparison with a heuristic

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In this research, we aim to assign jobs, having different processing and release times, to identical parallel machines in the most effective way. To do so; firstly we made a literature review to see what other researchers have done in this area. Secondly, we proposed three genetic algorithms each having different crossover methods. And at the end; we examined those three algorithms and also a heuristic which we already proposed and tested before. Based on the job size and machine size, some algorithms performed better results than others. © 2010 IEEE.

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