A genetic algorithm-based approach to single machine scheduling with general early–tardy penalty weights

It is in accordance with Just In Time philosophy to penalize early or tardy jobs. A genetic algorithm based optimal method of solving single machine scheduling problem with general early or tardy penalty weights is presented in the paper, which is composed of sequencing optimization and timing optimization algorithms. A new crossover operator is constructed for optimal sequencing search and an effective optimal timing algorithm proposed based on the characteristic analyses of penalty function. For different scale of problems, a lot of comparative computational experiments were done and the results manifested the method's effectiveness.