Supply chain optimisation using evolutionary algorithms
Marco Aurélio Falcone, Heitor Silvério Lopes, Leandro dos Santos Coelho · International Journal of Computer Applications in Technology · 2008
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.