Supply chain network optimization using a Tabu Search based heuristic

This paper discusses the implementation and evaluation of a heuristic based on Tabu Search to optimize a supply chain network. To this end, a single-source model proposed by Farias & Borenstein (2012) was implemented. The problem was solved by adapting the Lee & Kwon method (2010), exchangin...

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Detalles Bibliográficos
Autor: Borenstein, Denis
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:Ecuador
Institución:Universidad de Cuenca
Repositorio:Repositorio Universidad de Cuenca
OAI Identifier:oai:dspace.ucuenca.edu.ec:123456789/29166
Acceso en línea:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969759548&doi=10.1590%2f0104-530X1288-14&partnerID=40&md5=a9e7e22eccd4622871aa08db359f1afd
http://dspace.ucuenca.edu.ec/handle/123456789/29166
Access Level:acceso abierto
Palabra clave:Heuristic
Supply Chain Management
Supply Chain Network Optimization
Tabu Search
Descripción
Sumario:This paper discusses the implementation and evaluation of a heuristic based on Tabu Search to optimize a supply chain network. To this end, a single-source model proposed by Farias & Borenstein (2012) was implemented. The problem was solved by adapting the Lee & Kwon method (2010), exchanging distribution centers (DCs) and arcs to find the lowest cost for a supply chain network. Twenty-two instances proposed by Farias & Borenstein (2012) were solved and the results indicate that, for the scenarios, the method applied presented good computational performance, obtaining results with 81.03% reduction of the average processing time. However, there was an increase of 4.98% in the average cost of the solutions obtained through the heuristic method when compared with the optimal results. Finally, the problem was solved for four other instances with real features, proving the efficiency of this heuristic for large-scale problems, considering that all solutions were obtained in less than 2 minutes of processing.