Hybrid Particle SWARM Optimization for Solving Machine Time Scheduling Problem
International Journal of Computer and Information Technology • 2013
معلومات البحث
المؤلفون
A. A. El-sawy; A. A. Tharwat
الكلمات المفتاحية
Machine Time Scheduling, Particle SWARM optimization, Genetic Algorithm, Mutation, Crossover, Time Window
المجلة العلمية
International Journal of Computer and Information Technology
الناشر
Not Available
المجلد
02
العدد
03
الصفحات
364-375
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
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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