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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
18.10.2019
DOI
https://doi.org/10.7307/ptt.v31i5.3057
ISSUE
2019 (Vol 31), Issue 5
LICENSE
Copyright (c) 2024 Manman Li, Jian Lu, Wenxin Ma
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

A Hybrid Multi-objective Genetic Algorithm for Bi-objective Time Window Assignment Vehicle Routing Problem

Authors:

Manman Li

Jian Lu

Wenxin Ma

Keywords:vehicle routing, time window assignment, uncertain demand, time-dependent travel time, multi-objective genetic algorithms, local search

Abstract

Providing a satisfying delivery service is an important way to maintain the customers’ loyalty and further expand profits for manufacturers and logistics providers. Considering customers’ preferences for time windows, a bi-objective time window assignment vehicle routing problem has been introduced to maximize the total customers’ satisfaction level for assigned time windows and minimize the expected delivery cost. The paper designs a hybrid multi-objective genetic algorithm for the problem that incorporates modified stochastic nearest neighbour and insertion-based local search. Computational results show the positive effect of the hybridization and satisfactory performance of the metaheuristics. Moreover, the impacts of three characteristics are analysed including customer distribution, the number of preferred time windows per customer and customers’ preference type for time windows. Finally, one of its extended problems, the bi-objective time window assignment vehicle routing problem with time-dependent travel times has been primarily studied.

References

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    Li MM, Lu J, An Y. Bi-objective time window assignment vehicle routing problem considering customer preferences for time windows. Journal of Southeast University (Natural Science Edition). 2018;48(3): 568-575.

    Agatz N, Campbell A, Savelsbergh M. Time slot management in attended home delivery. Transportation Science. 2011;45(3): 435-449.

    Campbell AM, Savelsbergh M. Decision support for consumer direct grocery initiatives. Transportation Science. 2005;3(39): 313-327.

    Ehmke JF, Campbell AM. Customer acceptance mechanism for home deliveries in metropolitan areas. European Journal of Operational Research. 2014;233: 193-207.

    Baldacci R, Mingozzi A, Roberti R. Recent exact algorithms for solving the vehicle routing probl

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How to Cite
Li, M. (et al.) 2019. A Hybrid Multi-objective Genetic Algorithm for Bi-objective Time Window Assignment Vehicle Routing Problem. Traffic&Transportation Journal. 31, 5 (Oct. 2019), 513-525. DOI: https://doi.org/10.7307/ptt.v31i5.3057.

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