A Hybrid Dual-Population Genetic Algorithm for the Single Machine Maximum Lateness Problem

We consider the problem of scheduling a number of jobs, each job having a release time, a processing time and a due date, on a single machine with the objective of minimizing the maximum lateness. We developed a hybrid dual-population genetic algorithm and compared its performance with alternative methods on a new diverse data set. Extensions from a single to a dual population by taking problem specific characteristics into account can be seen as a stimulator to add diversity in the search process, which has a positive influence on the important balance between intensification and diversification. Based on a comprehensive literature study on genetic algorithms in single machine scheduling, a fair comparison of genetic operators was made.

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