A comparative analysis of constraint programming and metaheuristics for job-shop scheduling

The paper considers two kinds of optimization methods: constraint programming and metaheuristic search. It shows how each of the approaches can be applied to multiple instances of the job shop scheduling problem and compares the performance of these approaches among themselves and also under various parameter settings. It is shown that, given the instances of the problem and the parameter configurations considered in the paper, constraint programming clearly outperforms the other approaches. In its final section, the paper outlines further conclusions as well as suggestions for future work.