A genetic algorithm for solving the single machine earliness/tardiness problem with distinct due dates and ready times

The genetic algorithm (GA) is a heuristics, and commonly used to solve combinational problems. It has been proven to have high effectiveness and efficiency in many application areas. However, a successful GA application requires adapting the algorithm to the characteristics of a problem. In the past decades, various articles on single machine earliness and tardiness (SET) problem using a heuristic approaching have been published. Yet, there are few research addressing the area of the SET problem with distinct due dates and ready times for jobs. In this paper, a designed GA, modified optimal timing procedure, which starts the searching with a feasible solution obtained by applying the EXP-ET rule developed by Ow and Morton is developed for the SET problem. Computational results in the provided experiment show that the designed GA improves the SET solution in both quality and efficiency.