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Optimization of vehicle routing problem with fatigue driving based on genetic algorithm

Authors:

Jiacheng Li,

Jiaoman Du,

Lei LiAuthors Info & Claims

RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems

Pages 37 - 42

https://doi.org/10.1145/3264746.3264782

Published: 09 October 2018 Publication History

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Abstract

In order to better solve the logistics distribution problems and improve customer satisfaction, aiming at minimizing total cost, the author adds a variable that restricts drivers' fatigue driving in the model, and builds a model of route optimization based on heterogeneous vehicles, so as to design a single-parent genetic algorithm for this model, and validates the algorithm by the delivery case of Japan Takkyubin Corporation. The numerical results of the example show that the logistics distribution route optimization scheme based on the single-parent genetic algorithm can meet the customer's cargo and time requirements, and can reduce vehicle use costs, save early or late penalty costs, and improve the company's economic interests. This study provides new solution ideas for improving delivery issues.

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Cited By

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Ting LTeng SWu SChuang K(2022)Interactive planning of revisiting-free itinerary for signed-for deliveryInternational Journal of Data Science and Analytics10.1007/s41060-022-00333-014:4(439-456)Online publication date: 26-May-2022
https://doi.org/10.1007/s41060-022-00333-0
Teng SWu SChuang K(2019)Optimal Delivery Routing in Road Network With Occupancy Detection2019 20th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2019.00122(575-580)Online publication date: Jun-2019
https://doi.org/10.1109/MDM.2019.00122

Index Terms

Optimization of vehicle routing problem with fatigue driving based on genetic algorithm
1. Applied computing
  1. Operations research
    1. Transportation

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Published In

RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems

October 2018

355 pages

ISBN:9781450358859

DOI:10.1145/3264746

Conference Chair:
Chih-Cheng Hung
Kennesaw State University
,
General Chair:
Lamjed Ben Said
University of Tunis, Tunisia

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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KISM: Korean Institute of Smart Media

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Association for Computing Machinery

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Published: 09 October 2018

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RACS '18: International Conference on Research in Adaptive and Convergent Systems

October 9 - 12, 2018

Hawaii, Honolulu

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Ting LTeng SWu SChuang K(2022)Interactive planning of revisiting-free itinerary for signed-for deliveryInternational Journal of Data Science and Analytics10.1007/s41060-022-00333-014:4(439-456)Online publication date: 26-May-2022
https://doi.org/10.1007/s41060-022-00333-0
Teng SWu SChuang K(2019)Optimal Delivery Routing in Road Network With Occupancy Detection2019 20th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2019.00122(575-580)Online publication date: Jun-2019
https://doi.org/10.1109/MDM.2019.00122

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Improved Genetic Algorithm for Vehicle Routing Problem with Time Windows

An Improved Genetic Algorithm for Vehicle Routing Problem with Time-Window

A label based ant colony algorithm for heterogeneous vehicle routing with mixed backhaul

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