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

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  • Soofi, Mansour
  • Mohseni, Maryam

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.

Suggested Citation

  • Soofi, Mansour & Mohseni, Maryam, 2017. "Production Planning Optimization Using Genetic Algorithm and Particle Swarm Optimization (Case Study: Soofi Tea Factory)," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 7(3), September.
    • Handle: RePEc:ags:ijamad:292502
    DOI: 10.22004/ag.econ.292502
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    Keywords

    Production Economics;

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