Document Type: Case Report

Authors

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

2 PhD in Industrial Management, Tehran University

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 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.

Highlights

One of the most important tasks of production management is production planning.

The production plan is a type of prediction.

Classical and traditional optimization methods have failed in solving complex optimization problems.

Genetic algorithms and Particle Swarm Optimization method that are designed to find the global optimal solution to complex problems.

The results indicated the superiority of Particle swarm optimization algorithm in the tea industry.

Keywords

Main Subjects

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