Abstract
This paper studies an identical parallel machine scheduling problem with multiple objective functions (i.e. both regular and non-regular objective functions), and proposes a genetic algorithm (GA) approach to generate a set of the Pareto-optimal schedules. In the paper, several methods of generating the Pareto-optimal solutions for ordinary multi-objective optimization problems by using GAs are briefly reviewed, and then, a way of applying GAs to the scheduling problem is described. Finally, through computational experiments, the effectiveness of the proposed method is shown.
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