An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries

Zachariadis, EE; Tarantilis, CD; Kiranoudis, CT

dc.contributor.author	Zachariadis, EE	en
dc.contributor.author	Tarantilis, CD	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:58:51Z
dc.date.available	2014-03-01T01:58:51Z
dc.date.issued	2009	en
dc.identifier.issn	0377-2217	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28753
dc.subject	Vehicle routing	en
dc.subject	Simultaneous pick-ups and deliveries	en
dc.subject	Adaptive memory	en
dc.subject.classification	Management	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	HEURISTIC ALGORITHMS	en
dc.subject.other	SINGLE	en
dc.subject.other	DEPOT	en
dc.title	An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	This paper deals with a routing problem variant which considers Customers to simultaneously require delivery and pick-up services. The examined problem is referred to as the Vehicle Routing Problem with Simultaneous Pick-ups and Deliveries (VRPSPD). VRPSPD is an NP-hard combinatorial optimization problem, practical large-scale instances of which cannot be solved by exact solution methodologies within acceptable computational times. Our interest was therefore focused on metaheuristic solution approaches. In specific, we introduce an Adaptive Memory (AM) algorithmic framework which collects and combines promising solution features to generate high-quality solutions. The proposed strategy employs an innovative memory mechanism to systematically maximize the amount of routing information extracted from the AM, in order to drive the search towards diverse regions of the solution space. Our metaheuristic development was tested on numerous VRPSPD instances involving from 50 to 400 customers. It proved to be rather effective and efficient, as it produced high-quality solutions, requiring limited computational effort. Furthermore, it managed to produce several new best solutions. (C) 2009 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	EUROPEAN JOURNAL OF OPERATIONAL RESEARCH	en
dc.identifier.isi	ISI:000271936000010	en
dc.identifier.volume	202	en
dc.identifier.issue	2	en
dc.identifier.spage	401	en
dc.identifier.epage	411	en