Production Planning Optimization Using Genetic Algorithm and Particle Swarm Optimization (Case Study: Soofi Tea Factory)

International Journal of Agricultural Management and Development

مقاله 12، دوره 7، شماره 3، آذر 2017، صفحه 395-410   

نوع مقاله: Case Report

نویسندگان

Mansour Soufi^{* 1}؛ Maryam Mohseni²

¹Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran

²PhD in Industrial Management, Tehran University

چکیده

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 this study, 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.

کلیدواژه‌ها

Production Planning؛ Genetic algorithm؛ particle swarm optimization algorithm؛ Securities and Exchange Organization

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