Production PlanningOptimization UsingGeneticAlgorithm and Particle Swarm Optimization (Case Study: Soofi Tea Factory)

• Main Authors: Mansour Soofi, Maryam Mohsen
• Format: Article
• Language: English
• Published: Islamic Azad University 2017-09-01
• Series: International Journal of Agricultural Management and Development
• Subjects: production planning; Genetic algorithm; Particle Swarm Optimization Algorithm; SecuritiesandExchange Organization
• Online Access: http://ijamad.iaurasht.ac.ir/article_530260_985f507512ddf6d3c2ebf30560d1caad.pdf

Production planning includes complex topics of production and operation management that according to expansion of decision-making methods, have been considerably developed. Nowadays, managers use innovative approaches to solving problems of production planning. Given that the production plan is a type of prediction, models should be such that the slightest deviation from their reality. In order to minimize deviations from the values stated in the tea industry, two Particle Swarm optimization algorithm and genetic algorithm were used to solve the model. The data were obtained through interviews with Securities and Exchange Organization and those in financial units, industrial, commercial, and production. The results indicated the superiority of birds swarm optimization algorithm in the tea industry