Production PlanningOptimization UsingGeneticAlgorithm and Particle Swarm Optimization (Case Study: Soofi Tea Factory)
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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Islamic Azad University
2017-09-01
|
| Series: | International Journal of Agricultural Management and Development |
| Subjects: | |
| Online Access: | http://ijamad.iaurasht.ac.ir/article_530260_985f507512ddf6d3c2ebf30560d1caad.pdf |
| Summary: | 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 |
|---|---|
| ISSN: | 2159-5852 2159-5860 |