An open vehicle routing problem metaheuristic for examining wide solution neighborhoods

Zachariadis, EE; Kiranoudis, CT

dc.contributor.author	Zachariadis, EE	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:32:44Z
dc.date.available	2014-03-01T01:32:44Z
dc.date.issued	2010	en
dc.identifier.issn	0305-0548	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20213
dc.subject	Computational complexity	en
dc.subject	Metaheuristics	en
dc.subject	Open vehicle routing	en
dc.subject	Tabu search	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Candidate solution	en
dc.subject.other	Computational effort	en
dc.subject.other	Customer demands	en
dc.subject.other	Delivery service	en
dc.subject.other	Descriptors	en
dc.subject.other	Fibonacci heap	en
dc.subject.other	Insertions and deletions	en
dc.subject.other	Local search	en
dc.subject.other	Local search operators	en
dc.subject.other	Metaheuristic	en
dc.subject.other	Metaheuristics	en
dc.subject.other	Minimum cost	en
dc.subject.other	Open vehicle routing	en
dc.subject.other	Open vehicle routing problems	en
dc.subject.other	Practical transportation	en
dc.subject.other	Priority queues	en
dc.subject.other	Computational complexity	en
dc.subject.other	Heuristic methods	en
dc.subject.other	Network routing	en
dc.subject.other	Routing algorithms	en
dc.subject.other	Tabu search	en
dc.subject.other	Vehicles	en
dc.subject.other	Vehicle routing	en
dc.title	An open vehicle routing problem metaheuristic for examining wide solution neighborhoods	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cor.2009.06.021	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cor.2009.06.021	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	This paper examines a practical transportation model known as the open vehicle routing problem (OVRP). OVRP aims at designing the minimum cost set of routes originating from a central depot for satisfying customer demand. Vehicles do not need to return to the depot after completing their delivery services. In methodological terms, we propose an innovative local search metaheuristic which examines wide solution neighborhoods. To explore these wide neighborhoods within reasonable computational effort, local search moves are statically encoded into static move descriptor (SMD) entities. When a local search operator is applied to the candidate solution, only a limited solution part is modified. Therefore, to explore the next neighborhood only the tentative moves that refer to this affected solution part have to be re-evaluated, or in other words, only a subset of the SMD instances has to be updated, according to the modified solution state. The conducted search is efficiently performed by storing the SMD entities in Fibonacci heaps, which are special priority queue structures offering fast minimum retrievals, insertions and deletions. To diversify the search, we employ a tabu scheme and a penalization strategy, both compatible with the SMD design. The proposed metaheuristic was tested on well-known OVRP instances, for two objective configurations. The first one primarily aims at minimizing the number of routes and secondarily minimizing the routing cost, whereas the second one only aims at minimizing the cost of the generated route set. For both configurations, it managed to produce fine results improving several previously best-known solutions. (C) 2009 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Computers and Operations Research	en
dc.identifier.doi	10.1016/j.cor.2009.06.021	en
dc.identifier.isi	ISI:000272058100011	en
dc.identifier.volume	37	en
dc.identifier.issue	4	en
dc.identifier.spage	712	en
dc.identifier.epage	723	en