Comparison of Particle SWARM Optimization, Genetic Algorithm and Max separable Technique for Machine Time Scheduling Problem | ||||
| The International Conference on Mathematics and Engineering Physics | ||||
| Article 13, Volume 5, International Conference on Mathematics and Engineering Physics (ICMEP-5), May 2010, Page 1-10 PDF (317.2 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/icmep.2010.29808 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| A. A. El-sawy; A. A. Tharwat | ||||
| Abstract | ||||
| Abstract In this paper we deal with a multi cycle machine time scheduling problem (MTSP) to find the best starting time for each machine in each cycle. We introduce an algorithm by using the particle SWARM optimization (PSO) and Genetic algorithm to solve the MTSP. A comparison between PSO, GA and max-separable technique will be introduced to find the best solution which is the best starting time respect to its time window for each machine in each cycle and respect to the set of precedence machines to minimize the penalty cost. | ||||
| Keywords | ||||
| Machine Time Scheduling; Particle Swarm Optimization; Genetic Algorithm; Max-separable; Time Window | ||||
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