Firefly Algorithm for Supply Chain Optimization
The firefly algorithm is one of the best latest bio-inspired algorithms, which proved its performance in solving continuous and discrete optimization problems. This paper presents a more detailed comparison study using a set of test functions. The main goal is the application of Firefly algorithm (F...
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| Published in | Lobachevskii journal of mathematics Vol. 39; no. 3; pp. 355 - 367 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Moscow
Pleiades Publishing
01.04.2018
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1995-0802 1818-9962 |
| DOI | 10.1134/S1995080218030125 |
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| Abstract | The firefly algorithm is one of the best latest bio-inspired algorithms, which proved its performance in solving continuous and discrete optimization problems. This paper presents a more detailed comparison study using a set of test functions. The main goal is the application of Firefly algorithm (FA) to solve Lot size optimization in supply chain management which is the most complex part of stock management process. A complexity that comes from the conflict between the minimization of the costs and the maximization of the level of service. For these reason, the traditional methods of lot size control have to deal with the explosion of new needs related to supply chain evolution. The optimal solutions obtained by FA are far better than the best solutions obtained by deterministic methods analyzed in the literature. |
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| AbstractList | The firefly algorithm is one of the best latest bio-inspired algorithms, which proved its performance in solving continuous and discrete optimization problems. This paper presents a more detailed comparison study using a set of test functions. The main goal is the application of Firefly algorithm (FA) to solve Lot size optimization in supply chain management which is the most complex part of stock management process. A complexity that comes from the conflict between the minimization of the costs and the maximization of the level of service. For these reason, the traditional methods of lot size control have to deal with the explosion of new needs related to supply chain evolution. The optimal solutions obtained by FA are far better than the best solutions obtained by deterministic methods analyzed in the literature. |
| Author | Elkettani, Youssfi Hachimi, Hanaa Amine, Aouatif Benmamoun, Zoubida Elkhechafi, Mariam |
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| Keywords | Lot Size Metaheuristics Supply Chain Firefly algorithm Optimization |
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| SubjectTerms | Algebra Algorithms Analysis Complexity Control methods Geometry Heuristic methods Mathematical Logic and Foundations Mathematics Mathematics and Statistics Optimization Probability Theory and Stochastic Processes Supply chains |
| Title | Firefly Algorithm for Supply Chain Optimization |
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