• 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