A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem

Full truckload transportation (FTL) in the form of freight containers represents one of the most important transportation modes in international trade. Due to large volume and scale, in FTL, delivery time is often less critical but cost and service quality are crucial. Therefore, efficiently solving...

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Main Authors: Xue, Ning, Bai, Ruibin, Qu, Rong, Aickelin, Uwe
Format: Article
Language:English
Published: Elsevier B.V. 2020
Subjects:
Online Access:https://eprints.nottingham.ac.uk/64126/
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author Xue, Ning
Bai, Ruibin
Qu, Rong
Aickelin, Uwe
author_facet Xue, Ning
Bai, Ruibin
Qu, Rong
Aickelin, Uwe
author_sort Xue, Ning
building Nottingham Research Data Repository
collection Online Access
description Full truckload transportation (FTL) in the form of freight containers represents one of the most important transportation modes in international trade. Due to large volume and scale, in FTL, delivery time is often less critical but cost and service quality are crucial. Therefore, efficiently solving large scale multiple shift FTL problems is becoming more and more important and requires further research. In one of our earlier studies, a set covering model and a three-stage solution method were developed for a multi-shift FTL problem. This paper extends the previous work and presents a significantly more efficient approach by hybridising pricing and cutting strategies with metaheuristics (a variable neighbourhood search and a genetic algorithm). The metaheuristics were adopted to find promising columns (vehicle routes) guided by pricing and cuts are dynamically generated to eliminate infeasible flow assignments caused by incompatible commodities. Computational experiments on real-life and artificial benchmark FTL problems showed superior performance both in terms of computational time and solution quality, when compared with previous MIP based three-stage methods and two existing metaheuristics. The proposed cutting and heuristic pricing approach can efficiently solve large scale real-life FTL problems.
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spelling nottingham-641262020-12-18T08:47:48Z https://eprints.nottingham.ac.uk/64126/ A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem Xue, Ning Bai, Ruibin Qu, Rong Aickelin, Uwe Full truckload transportation (FTL) in the form of freight containers represents one of the most important transportation modes in international trade. Due to large volume and scale, in FTL, delivery time is often less critical but cost and service quality are crucial. Therefore, efficiently solving large scale multiple shift FTL problems is becoming more and more important and requires further research. In one of our earlier studies, a set covering model and a three-stage solution method were developed for a multi-shift FTL problem. This paper extends the previous work and presents a significantly more efficient approach by hybridising pricing and cutting strategies with metaheuristics (a variable neighbourhood search and a genetic algorithm). The metaheuristics were adopted to find promising columns (vehicle routes) guided by pricing and cuts are dynamically generated to eliminate infeasible flow assignments caused by incompatible commodities. Computational experiments on real-life and artificial benchmark FTL problems showed superior performance both in terms of computational time and solution quality, when compared with previous MIP based three-stage methods and two existing metaheuristics. The proposed cutting and heuristic pricing approach can efficiently solve large scale real-life FTL problems. Elsevier B.V. 2020-10-30 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/64126/1/A%20hybrid%20pricing%20and%20cutting%20approach%20for%20the%20multi-shift%20full%20truckload%20vehicle%20routing%20problem.pdf Xue, Ning, Bai, Ruibin, Qu, Rong and Aickelin, Uwe (2020) A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem. European Journal of Operational Research . ISSN 0377-2217 Transportation; Full truckload transport; Column generation; Pricing and cutting; Metaheuristics http://dx.doi.org/10.1016/j.ejor.2020.10.037 doi:10.1016/j.ejor.2020.10.037 doi:10.1016/j.ejor.2020.10.037
spellingShingle Transportation; Full truckload transport; Column generation; Pricing and cutting; Metaheuristics
Xue, Ning
Bai, Ruibin
Qu, Rong
Aickelin, Uwe
A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title_full A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title_fullStr A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title_full_unstemmed A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title_short A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
title_sort hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem
topic Transportation; Full truckload transport; Column generation; Pricing and cutting; Metaheuristics
url https://eprints.nottingham.ac.uk/64126/
https://eprints.nottingham.ac.uk/64126/
https://eprints.nottingham.ac.uk/64126/