IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION FOR JOB-SHOP SCHEDULING PROBLEMS
The Job-shop Scheduling Problems (JSP) is a typical production scheduling problem widely applied as a single-objective optimization in existing research. However, this is not suitable for cases in the real world, which normally consist of multi-objective criteria. In this paper, a multi-objective Particle Swarm Optimization (MOPSO) for solving JSP is developed, where it involves three key MOPSO attributes to be improved as identified from the literature which are diversity of swarm solutions, exploitation/exploration mechanisms throughout the search process and premature convergence. In order to address the issues related to these attributes, improvement strategies are implemented that include reinitialization of particles, systematic switch of best solutions and Tabu search-based mutation. The computational results in solving benchmark instances demonstrated that the improved MOPSO performs well in terms of finding non-dominated solutions in different regions of the Pareto fronts with a wider spread and producing a higher percentage of solutions in comparison with other established techniques.
Authors who publish with this journal agree to the following terms:
- Authors transfer copyright to the publisher as part of a journal publishing agreement with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after the manuscript is accepted, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).