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

الموضوعات :

منصور صوفی ¹ ( گروه مدیریت صنعتی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران )
مریم محسنی ² ( دکتری مدیدت صنعتی، دانشگاه تهران )

تاريخ الإرسال : 10 الأحد , ذو الحجة, 1437 تاريخ التأكيد : 18 الأحد , شعبان, 1438 تاريخ الإصدار : 10 الجمعة , ذو الحجة, 1438

الکلمات المفتاحية: Genetic algorithm, particle swarm optimization algorithm, Securities and Exchange Organization, Production Planning,

ملخص المقالة :

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.

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