Mostra el registre parcial de l'element Ramalhinho-Lourenço, Helena
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa 2017-07-26T10:50:01Z 2017-07-26T10:50:01Z 2001-03-01
dc.identifier.citation Metaheuristics Optimization via Memory and Evolution, C. Rego and B. Alidaee (eds.), Kluwer Academic Publishers, pp. 329-356, 2005
dc.description.abstract In today s highly competitive and global marketplace the pressure on organizations to find new ways to create and deliver value to customers grows ever stronger. In the last two decades, logistics and supply chain has moved to the center stage. There has been a growing recognition that it is through an effective management of the logistics function and the supply chain that the goal of cost reduction and service enhancement can be achieved. The key to success in Supply Chain Management (SCM) require heavy emphasis on integration of activities, cooperation, coordination and information sharing throughout the entire supply chain, from suppliers to customers. To be able to respond to the challenge of integration there is the need of sophisticated decision support systems based on powerful mathematical models and solution techniques, together with the advances in information and communication technologies. The industry and the academia have become increasingly interested in SCM to be able to respond to the problems and issues posed by the changes in the logistics and supply chain. We present a brief discussion on the important issues in SCM. We then argue that metaheuristics can play an important role in solving complex supply chain related problems derived by the importance of designing and managing the entire supply chain as a single entity. We will focus specially on the Iterated Local Search, Tabu Search and Scatter Search as the ones, but not limited to, with great potential to be used on solving the SCM related problems. We will present briefly some successful applications.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 538
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.title Supply chain management: An opportunity for metaheuristics
dc.title.alternative Logistics Management: an opportunity for Metaheuristics
dc.type info:eu-repo/semantics/workingPaper 2017-07-23T02:06:02Z
dc.subject.keyword supply chain management
dc.subject.keyword metaheuristics
dc.subject.keyword iterated local search
dc.subject.keyword tabu search and scatter search
dc.subject.keyword Operations Management
dc.rights.accessRights info:eu-repo/semantics/openAccess

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