Advanced scheduling problem using constraint programming techniques in the supply chain management environment

In this paper we consider a preemptive and non-preemptive scheduling model as one of the advanced scheduling problems considered by a constraint programming technique and propose a new genetic algorithm (GA) considering simultaneously the preemptive and non-preemptive cases of the activities of jobs under single machine job-shop scheduling problems. In the proposed GA, we develop a new method for representing the chromosome of GA. For various comparisons, we also propose the hybrid GAs with the proposed GA and conventional sequencing rules. These hybrid GAs are applied to several job-shop scheduling problems under a single machine. Experiment results show that the proposed hybrid GA with a conventional sequencing rule outperforms the proposed GA and other conventional sequencing rules.