The pallet-packing vehicle routing problem

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	2014-03-01T02:14:50Z
dc.date.available	2014-03-01T02:14:50Z
dc.date.issued	2012	en
dc.identifier.issn	00411655	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30136
dc.subject	Heuristic computing	en
dc.subject	Tabu search	en
dc.subject	Three-dimensional bin packing	en
dc.subject	Vehicle routing	en
dc.title	The pallet-packing vehicle routing problem	en
heal.type	journalArticle	en
heal.identifier.primary	10.1287/trsc.1110.0373	en
heal.identifier.secondary	http://dx.doi.org/10.1287/trsc.1110.0373	en
heal.publicationDate	2012	en
heal.abstract	This article introduces and solves a new transportation problem called the pallet-packing vehicle routing problem (PPVRP). PPVRP belongs to the category of practical routing models integrated with loading constraints, and assumes that customers raise a deterministic demand in the form of three-dimensional rectangular boxes. It is aimed at determining the optimal vehicle routes for satisfying customer demand. Regarding the packing aspects, transported boxes are not directly loaded into the vehicle-loading spaces; instead, they are feasibly stacked into pallets that are then loaded onto the vehicles before initiating their tours. Belonging to the class of combined routing and packing models, PPVRP is very hard to be optimally solved within manageable computational time; thus, we focused on heuristic approaches for both the routing and packing aspects of the problem. More specifically, PPVRP is solved via a local search metaheuristic strategy based on the regional aspiration criteria of tabu search. To determine feasible pallet-packing arrangements, we employ an efficient packing heuristic approach. The algorithm is accelerated by storing collected packing feasibility information into memory components. The proposed solution approach is tested on newly introduced benchmark instances derived from well-studied vehicle routing data sets, as well as real-world problems. © 2012 INFORMS.	en
heal.journalName	Transportation Science	en
dc.identifier.doi	10.1287/trsc.1110.0373	en
dc.identifier.volume	46	en
dc.identifier.issue	3	en
dc.identifier.spage	341	en
dc.identifier.epage	358	en