A Hybrid Metaheuristic Algorithm for the Integrated Vehicle Routing and Three-Dimensional Container-Loading Problem

Tarantilis, CD; Zachariadis, EE; Kiranoudis, CT

dc.contributor.author	Tarantilis, CD	en
dc.contributor.author	Zachariadis, EE	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:29:33Z
dc.date.available	2014-03-01T01:29:33Z
dc.date.issued	2009	en
dc.identifier.issn	1524-9050	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19304
dc.subject	Fleet management	en
dc.subject	guided local search (GLS)	en
dc.subject	tabu search (TS)	en
dc.subject	vehicle routing and packing integration	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Transportation Science & Technology	en
dc.subject.other	TABU SEARCH	en
dc.subject.other	CONSTRAINTS	en
dc.title	A Hybrid Metaheuristic Algorithm for the Integrated Vehicle Routing and Three-Dimensional Container-Loading Problem	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TITS.2009.2020187	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TITS.2009.2020187	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	This paper examines a recently addressed practical variant of the capacitated vehicle routing problem (VRP) called the Capacitated Vehicle Routing Problem with 3-D Loading Constraints (3L-CVRP). This problem considers customer demand to be formed by 3-D rectangular items. Additional loading constraints often encountered in real-life applications of transportation logistics are imposed on the examined problem model. In addition to 3L-CVRP, we also introduce and solve a new practical problem version that was dictated by a transportation logistics company and covers cases in which transported items are manually unloaded from the loading spaces of the vehicles. Both problem versions are solved by a hybrid metaheuristic methodology that combines the strategies of tabu search (TS) and guided local search (GLS). The loading characteristics are tackled by employing a collection of packing heuristics. The proposed algorithm's robustness was tested for both problem versions, solving benchmark instances derived from the literature and new benchmark problems with diverse features in terms of customer set size and transported-item dimensions. It produced fine results, improving most of the best solutions that were previously reported.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS	en
dc.identifier.doi	10.1109/TITS.2009.2020187	en
dc.identifier.isi	ISI:000266778300006	en
dc.identifier.volume	10	en
dc.identifier.issue	2	en
dc.identifier.spage	255	en
dc.identifier.epage	271	en