Title of article :
Production Planning Optimization Using Genetic Algorithm and Particle Swarm Optimization (Case Study: Soofi Tea Factory)
Author/Authors :
Soofi, Mansour Department of Industrial Management - Rasht Branch , Islamic Azad University , Mohseni, Maryam Tehran University
Pages :
16
From page :
395
To page :
410
Abstract :
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.
Keywords :
production planning , Genetic algorithm , Particle Swarm Optimization Algorithm , Securitiesand Exchange Organization
Journal title :
Astroparticle Physics
Serial Year :
2017
Record number :
2431665
Link To Document :
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