There have been extensive works dealing with genetic algorithms (GAs) for seeking optimal solutions of shop scheduling problems. Due to the NP hardness, the time cost is always heavy. With the development of high performance computing (HPC) in last decades, the interest has been focused on parallel GAs for shop scheduling problems. In this paper, we present the state of the art with respect to the recent works on solving shop scheduling problems using parallel GAs. It showcases the most representative publications in this field by the categorization of parallel GAs and analyzes their designs based on the frameworks.
- Pub Date:
- April 2019
- Computer Science - Distributed;
- and Cluster Computing
- 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May 2018, Vancouver, France. IEEE, pp.629-636