Multi-item fuzzy economic production quantity model with multiple deliveries
Autor: | Reza Moghdani, Shib Sankar Sana, Hamid Shahbandarzadeh |
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Rok vydání: | 2019 |
Předmět: |
Inventory control
0209 industrial biotechnology Mathematical optimization Mathematical model Computer science Computational intelligence 02 engineering and technology Economic production quantity Fuzzy logic Theoretical Computer Science 020901 industrial engineering & automation Metaheuristic algorithms 0202 electrical engineering electronic engineering information engineering Fuzzy number 020201 artificial intelligence & image processing Geometry and Topology Metaheuristic Software |
Zdroj: | Soft Computing. 24:10363-10387 |
ISSN: | 1433-7479 1432-7643 |
Popis: | Inventory control is one of the most critical issues in corporate management. Many mathematical models have been developed to optimize control strategies for the companies’ inventory. Economic production quantity (EPQ) is one of the classic models for inventory control, which is widely used. To deal with the uncertainty in the real world, we need to develop new and useful models for modeling systems of inventory management. In such cases, fuzzy models play a unique role in the field of inventory management. The main contribution of this study is to apply some well-known metaheuristic to solve an extended EPQ model based on fuzzy numbers considering multiple deliveries. This study aims to develop an EPQ model by considering demand as triangular fuzzy numbers and multiple deliveries (delivering in multiple packages) and by considering limitations in warehouse space as well as the total number of orders. Given these conditions, EPQ costs are calculated, and new modeling is presented. The obtained fuzzy model has been simplified by using the $$ \alpha{\text{-cut}} $$ and changing the variables, and finally, the most well-known metaheuristic algorithms, GA, PSO, GWO, and ICA, are applied in different problem sizes, and obtained results are analyzed in terms of minimizing cost function and CPU time. The result of this paper shows that GWO has superior performance in terms of various parameters. |
Databáze: | OpenAIRE |
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