Abstract
This work considers scheduling problems on single and parallel machines with arbitrary processing times and independent jobs, to minimize the sum of earliness-tardiness penalties. A Genetic Algorithm with a smart local search approach is presented, a 2-opt neighborhood-based with GPI moves and tie-breaking criteria, in a single sequence representation for single and multi-machine instances. Computational experiments are performed on Tanaka's instances for single machine, achieving all optimal solutions obtained by an IP exact method, for 40, 50, and 100 jobs. Moreover, our method is also suitable for dealing with multi-machine instances, achieving good solutions in a reasonable execution time, for 40, 50, and 100 jobs, with 2, 4, and 10 machines.
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