Genetic algorithms for vehicle routing problem with recourse cost model

Jun Qi Chen, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper deals with the vehicle routing problem involved with System fuzzy vehicle travel times. A two-stage possibility programming model is formulated and the influence of the fuzziness of travel times and service times is treated as recourse cost. By introducing the generalized mean value to define the Fuzzy Mean, the recourse possibility programming model can be transformed into an ordinary programming problem (Slowinski and Hapke in Scheduling under fuzziness. Physics, Heidelberg, 2000) and then a solution method based on Genetic Algorithms is proposed to give the optimal solution of the problem. Finally, some examples are given to illustrate the two-stage model and the solution algorithm.

Original languageEnglish
Title of host publication19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management
Pages903-916
Number of pages14
DOIs
Publication statusPublished - 2013
Event19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management - Changsha
Duration: 2012 Oct 272012 Oct 29

Other

Other19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management
CityChangsha
Period12/10/2712/10/29

Fingerprint

Vehicle routing
Genetic algorithms
Travel time
Costs
Fuzzy systems
Physics
Scheduling

Keywords

  • Genetic algorithms
  • Possibility programming
  • Recourse cost
  • Vehicle routing

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Chen, J. Q., & Murata, T. (2013). Genetic algorithms for vehicle routing problem with recourse cost model. In 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management (pp. 903-916) https://doi.org/10.1007/978-3-642-38442-4_96

Genetic algorithms for vehicle routing problem with recourse cost model. / Chen, Jun Qi; Murata, Tomohiro.

19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management. 2013. p. 903-916.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, JQ & Murata, T 2013, Genetic algorithms for vehicle routing problem with recourse cost model. in 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management. pp. 903-916, 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management, Changsha, 12/10/27. https://doi.org/10.1007/978-3-642-38442-4_96
Chen JQ, Murata T. Genetic algorithms for vehicle routing problem with recourse cost model. In 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management. 2013. p. 903-916 https://doi.org/10.1007/978-3-642-38442-4_96
Chen, Jun Qi ; Murata, Tomohiro. / Genetic algorithms for vehicle routing problem with recourse cost model. 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management. 2013. pp. 903-916
@inproceedings{09ff0a88bc6b41d1b96cf317999297c4,
title = "Genetic algorithms for vehicle routing problem with recourse cost model",
abstract = "This paper deals with the vehicle routing problem involved with System fuzzy vehicle travel times. A two-stage possibility programming model is formulated and the influence of the fuzziness of travel times and service times is treated as recourse cost. By introducing the generalized mean value to define the Fuzzy Mean, the recourse possibility programming model can be transformed into an ordinary programming problem (Slowinski and Hapke in Scheduling under fuzziness. Physics, Heidelberg, 2000) and then a solution method based on Genetic Algorithms is proposed to give the optimal solution of the problem. Finally, some examples are given to illustrate the two-stage model and the solution algorithm.",
keywords = "Genetic algorithms, Possibility programming, Recourse cost, Vehicle routing",
author = "Chen, {Jun Qi} and Tomohiro Murata",
year = "2013",
doi = "10.1007/978-3-642-38442-4_96",
language = "English",
isbn = "9783642384417",
pages = "903--916",
booktitle = "19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management",

}

TY - GEN

T1 - Genetic algorithms for vehicle routing problem with recourse cost model

AU - Chen, Jun Qi

AU - Murata, Tomohiro

PY - 2013

Y1 - 2013

N2 - This paper deals with the vehicle routing problem involved with System fuzzy vehicle travel times. A two-stage possibility programming model is formulated and the influence of the fuzziness of travel times and service times is treated as recourse cost. By introducing the generalized mean value to define the Fuzzy Mean, the recourse possibility programming model can be transformed into an ordinary programming problem (Slowinski and Hapke in Scheduling under fuzziness. Physics, Heidelberg, 2000) and then a solution method based on Genetic Algorithms is proposed to give the optimal solution of the problem. Finally, some examples are given to illustrate the two-stage model and the solution algorithm.

AB - This paper deals with the vehicle routing problem involved with System fuzzy vehicle travel times. A two-stage possibility programming model is formulated and the influence of the fuzziness of travel times and service times is treated as recourse cost. By introducing the generalized mean value to define the Fuzzy Mean, the recourse possibility programming model can be transformed into an ordinary programming problem (Slowinski and Hapke in Scheduling under fuzziness. Physics, Heidelberg, 2000) and then a solution method based on Genetic Algorithms is proposed to give the optimal solution of the problem. Finally, some examples are given to illustrate the two-stage model and the solution algorithm.

KW - Genetic algorithms

KW - Possibility programming

KW - Recourse cost

KW - Vehicle routing

UR - http://www.scopus.com/inward/record.url?scp=84891910540&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891910540&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-38442-4_96

DO - 10.1007/978-3-642-38442-4_96

M3 - Conference contribution

AN - SCOPUS:84891910540

SN - 9783642384417

SP - 903

EP - 916

BT - 19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management

ER -