A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector

Tarantilis, CD; Kiranoudis, CT

dc.contributor.author	Tarantilis, CD	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:25:40Z
dc.date.available	2014-03-01T01:25:40Z
dc.date.issued	2007	en
dc.identifier.issn	0377-2217	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17719
dc.subject	Construction project management	en
dc.subject	Industrial logistics	en
dc.subject	Metaheuristics	en
dc.subject	Vehicle routing system	en
dc.subject.classification	Management	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Adaptive algorithms	en
dc.subject.other	Heuristic methods	en
dc.subject.other	Metadata	en
dc.subject.other	Optimization	en
dc.subject.other	Problem solving	en
dc.subject.other	Project management	en
dc.subject.other	Tracking (position)	en
dc.subject.other	Construction project management	en
dc.subject.other	Industrial logistics	en
dc.subject.other	Metaheuristics	en
dc.subject.other	Vehicle routing problem (VRP)	en
dc.subject.other	Operations research	en
dc.title	A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ejor.2005.03.059	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ejor.2005.03.059	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	Effective routing of vehicles remains a focal goal of all modern enterprises, thriving for excellence in project management with minimal investment and operational costs. This paper proposes a metaheuristic methodology for solving a practical variant of the well-known Vehicle Routing Problem, called Heterogeneous Fixed Fleet VRP (HFFVRP). Using a two-phase construction heuristic, called GEneralized ROute Construction Algorithm (GEROCA), the proposed metaheuristic approach enhances its flexibility to easily adopt various operational constraints. Via this approach, two real-life distribution problems faced by a dairy and a construction company were tackled and formulated as HFFVRP. Computational results on the aforementioned case studies show that the proposed metaheuristic approach (a) consistently outperforms previous published metaheuristic approaches we have developed to solve the HFFVRP, and (b) substantially improves upon the current practice of the company. The key result that impressed both companies' management was the improvement over the bi-objective character of their problems: the minimization of the total distribution cost as well as the minimization of the number of the given heterogeneous number of vehicles used. (c) 2005 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	European Journal of Operational Research	en
dc.identifier.doi	10.1016/j.ejor.2005.03.059	en
dc.identifier.isi	ISI:000243794700015	en
dc.identifier.volume	179	en
dc.identifier.issue	3	en
dc.identifier.spage	806	en
dc.identifier.epage	822	en