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	2014-03-01T01:32:37Z
dc.date.available	2014-03-01T01:32:37Z
dc.date.issued	2010	en
dc.identifier.issn	03772217	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20197
dc.subject	Adaptive memory	en
dc.subject	Simultaneous pick-ups and deliveries	en
dc.subject	Vehicle routing	en
dc.subject.other	Adaptive memory	en
dc.subject.other	Algorithmic framework	en
dc.subject.other	Combinatorial optimization problems	en
dc.subject.other	Computational effort	en
dc.subject.other	Computational time	en
dc.subject.other	Exact solution	en
dc.subject.other	High-quality solutions	en
dc.subject.other	Memory mechanism	en
dc.subject.other	Metaheuristic	en
dc.subject.other	NP-hard	en
dc.subject.other	Routing information	en
dc.subject.other	Routing problems	en
dc.subject.other	Simultaneous pick-ups and deliveries	en
dc.subject.other	Solution approach	en
dc.subject.other	Solution space	en
dc.subject.other	Vehicle Routing Problems	en
dc.subject.other	Amplitude modulation	en
dc.subject.other	Combinatorial optimization	en
dc.subject.other	Communication channels (information theory)	en
dc.subject.other	Computational complexity	en
dc.subject.other	Heuristic methods	en
dc.subject.other	Network routing	en
dc.subject.other	Pickups	en
dc.subject.other	Routing algorithms	en
dc.subject.other	Vehicles	en
dc.subject.other	Vehicle routing	en
dc.title	An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ejor.2009.05.015	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ejor.2009.05.015	en
heal.publicationDate	2010	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. © 2009 Elsevier B.V. All rights reserved.	en
heal.journalName	European Journal of Operational Research	en
dc.identifier.doi	10.1016/j.ejor.2009.05.015	en
dc.identifier.volume	202	en
dc.identifier.issue	2	en
dc.identifier.spage	401	en
dc.identifier.epage	411	en