| Autor: |
John, Kurian, Paul, Brijesh, Noble, Jibin |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3134 Issue 1, p1-11, 11p |
| Abstrakt: |
In any supply chain, the cost of inventory makes up around 30% of the value of the product, which makes it one of the most crucial aspects of supply chain management. Several heuristic and metaheuristic inventory optimization techniques are widely used in management of supply chains, but there are lot of uncertain factors for inventory optimization and many techniques can be improved or adopted for better management of inventory. Genetic algorithm is one of the commonly used algorithms to manage inventory. Since it can be easily adapted and can handle multiple criteria, but it does not guarantee optimality. A serial supply chain with a supplier, manufacturer, distributor, and a retailer are considered in this paper. The inventory for a single product is managed by deploying periodic review base stock policy at each member of the supply chain. Three metaheuristic algorithms namely Genetic Algorithm, Crow Search Algorithm and Adaptive G-best Gravitational Search Algorithm are used to optimize the decision variables with the objective of minimising total cost. Experimental analysis is performed on all the algorithms and results obtained from the experimental studies are compared. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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