Bibliographic Details
| Title: |
Supply chain optimisation using evolutionary algorithms. |
| Authors: |
Falcone, Marco Aurelio1, Lopes, Heitor Silverio2, Coelho, Leandro Dos Santos3 |
| Source: |
International Journal of Computer Applications in Technology. 2008, Vol. 31 Issue 3/4, p158-167. 10p. |
| Subjects: |
Evaluation, Application logging (Computer science), Theory-practice relationship, Genetic algorithms, Numerical solutions to evolution equations, Evolutionary computation, Physical distribution of goods, Combinatorial optimization, Business logistics |
| Abstract: |
This paper describes the application of Evolutionary Algorithms (EAs) to the optimisation of a simplified supply chain in an integrated production-inventory-distribution system. The performance of four EAs (Genetic Algorithm (GA), Evolutionary Programming (EP), Evolution Strategies (ES) and Differential Evolution (DE)) was evaluated with numerical simulations. Results were also compared with other similar approaches in the literature. DE was the algorithm that led to better results, outperforming previously published solutions. The robustness of EAs in general, and the efficiency of DE, in particular, suggest their great utility for the supply chain optimisation problem, as well as for other logistics-related problems. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
