An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

Androutsopoulos, Konstantinos N. and Zografos, Konstantinos G. (2017) An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations. Transportation Research Part C: Emerging Technologies, 82. pp. 180-209. ISSN 0968-090X

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Abstract

The consideration of pollution in routing decisions gives rise to a new routing framework where measures of the environmental implications are traded off with business performance measures. To address this type of routing decisions, we formulate and solve a bi-objective time, load and path-dependent vehicle routing problem with time windows (BTL-VRPTW). The proposed formulation incorporates a travel time model representing realistically time varying traffic conditions. A key feature of the problem under consideration is the need to address simultaneously routing and path finding decisions. To cope with the computational burden arising from this property of the problem we propose a network reduction approach. Computational tests on the effect of the network reduction approach on determining non-dominated solutions are reported. A generic solution framework is proposed to address the BTL-VRPTW. The proposed framework combines any technique that creates capacity-feasible routes with a routing and scheduling method that aims to convert the identified routes to problem solutions. We show that transforming a set of routes to BTL-VRPTW solutions is equivalent to solving a bi-objective time dependent shortest path problem on a specially structured graph. We propose a backward label setting technique to solve the emerging problem that takes advantage of the special structure of the graph. The proposed generic solution framework is implemented by integrating the routing and scheduling method into an Ant Colony System algorithm. The accuracy of the proposed algorithm was assessed on the basis of its capability to determine minimum travel time and fuel consumption solutions. Although the computational results are encouraging, there is ample room for future research in algorithmic advances on addressing the proposed problem.

Item Type:
Journal Article
Journal or Publication Title:
Transportation Research Part C: Emerging Technologies
Additional Information:
This is the author’s version of a work that was accepted for publication in Transportation Research Part C: Emerging Technologies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Transportation Research Part C: Emerging Technologies, 82, 2017 DOI: 10.1016/j.trc.2017.06.013
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/aacsb/disciplinebasedresearch
Subjects:
ID Code:
86954
Deposited By:
Deposited On:
06 Jul 2017 10:38
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Sep 2020 03:58