Local search for the undirected capacitated arc routing problem with profits

Zachariadis, EE; Kiranoudis, CT

dc.contributor.author	Zachariadis, EE	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:35:57Z
dc.date.available	2014-03-01T01:35:57Z
dc.date.issued	2011	en
dc.identifier.issn	0377-2217	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21258
dc.subject	Arc routing with profits	en
dc.subject	Aspiration criteria	en
dc.subject	Local search	en
dc.subject	Metaheuristics	en
dc.subject.classification	Management	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Arc routing	en
dc.subject.other	Aspiration criteria	en
dc.subject.other	Capacitated arc routing problem	en
dc.subject.other	High quality	en
dc.subject.other	Local search	en
dc.subject.other	Meta heuristics	en
dc.subject.other	Metaheuristic	en
dc.subject.other	Neighborhood structure	en
dc.subject.other	Potential customers	en
dc.subject.other	Routing problems	en
dc.subject.other	Transportation network	en
dc.subject.other	Travel time	en
dc.subject.other	Earnings	en
dc.subject.other	Heuristic algorithms	en
dc.subject.other	Profitability	en
dc.subject.other	Tabu search	en
dc.title	Local search for the undirected capacitated arc routing problem with profits	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ejor.2010.09.039	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ejor.2010.09.039	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	This paper deals with a recently introduced routing problem variant called the undirected capacitated arc routing problem with profits (UCARPP). The UCARPP model considered in the present study is primarily aimed at generating the route set which maximizes the profit collected from a set of potential customers, represented by edges of the examined transportation network. The secondary objective is to minimize the total route travel time. The generated routes are subject both to capacity and travel time constraints. To tackle the examined problem, we propose a local search metaheuristic development which explores two solution neighborhood structures. The conducted search is effectively diversified by means of the promises concept which is based on the aspiration criteria used in tabu search approaches. The proposed algorithm was tested on UCARPP benchmark instances taken from the literature. It efficiently produced high-quality results, improving several previously best known solutions. (C) 2010 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.2010.09.039	en
dc.identifier.isi	ISI:000286853300024	en
dc.identifier.volume	210	en
dc.identifier.issue	2	en
dc.identifier.spage	358	en
dc.identifier.epage	367	en