Supply chain optimisation using evolutionary algorithms

Authors:
Marco Aurelio Falcone;Heitor Silverio Lopes;Leandro Dos Santos Coelho
Affiliations:
Tritec Motors, R. Ema Tanner de Andrade, 1892, Vila Ferrari – 83606-360, Campo Largo (PR), Brazil.;Federal Technological University of Parana/CPGEI, Av. 7 de setembro, 3165, 80230-901 Curitiba (PR), Brazil.;Pontifical Catholic University of Parana/PPGEPS/LAS, R. Imaculada Conceicao, 1155, 80215-901 Curitiba (PR), Brazil
Venue:
International Journal of Computer Applications in Technology
Year:
2008

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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.