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Prof. Ahmed Abouelyazed Elsawy Ali :: Publications:

Title:
Hybrid Particle SWARM Optimization for Solving Machine Time Scheduling Problem
Authors: A. A. El-sawy; A. A. Tharwat
Year: 2013
Keywords: Machine Time Scheduling, Particle SWARM optimization, Genetic Algorithm, Mutation, Crossover, Time Window
Journal: International Journal of Computer and Information Technology
Volume: 02
Issue: 03
Pages: 364-375
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

A hybrid particle swarm optimization (PSO) for multi-machine time scheduling problem (MTSP) with multicycles is proposed in this paper to choose the best starting time for each machine in each cycle under pre-described time window and a set of precedence machines for each machine; to minimize the total penalty cost. We developed hybrid algorithm by using a combination between PSO and Genetic Algorithms (GA), precisely the GA operators’ crossover and mutation. Based on experimental results for the developed hybrid algorithms, we can conclude that, the algorithm that combines PSO with mutation gives best solution for MTSP.

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