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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| 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 |
| 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. |
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