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Pareto-based Hybrid Multi-Objective Evolutionary Algorithm for Flexible Job-shop Scheduling Problem
| Content Provider | Semantic Scholar |
|---|---|
| Author | Nagamani, Mrs. Chandrasekaran, E. Saravanan, D. Shanthi |
| Copyright Year | 2013 |
| Abstract | In this paper, flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid evolutionary algorithm is proposed to obtain a large set of Pareto-optimal solutions in a reasonable run time. The algorithm utilizes from a local search heuristic for improving the chance of obtaining more number of global Pareto-optimal solutions. The solution method uses from a perturbed global criterion function for guiding the search direction of the hybrid algorithm. Computational experiences show that the hybrid algorithm has superior performance in contrast to previous studies. |
| File Format | PDF HTM / HTML |
| DOI | 10.9790/5728-0913645 |
| Alternate Webpage(s) | http://www.iosrjournals.org/iosr-jm/papers/Vol9-issue1/F0913645.pdf |
| Alternate Webpage(s) | https://doi.org/10.9790/5728-0913645 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
