Genetic algorithms for vehicle routing problem with recourse cost model

Jun Qi Chen; Tomohiro Murata

doi:10.1007/978-3-642-38442-4_96

Genetic algorithms for vehicle routing problem with recourse cost model

Jun Qi Chen^*, Tomohiro Murata

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	19th International Conference on Industrial Engineering and Engineering Management
Subtitle of host publication	Engineering Economics Management
Pages	903-916
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-642-38442-4_96
Publication status	Published - 2013
Externally published	Yes
Event	19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management - Changsha, China Duration: 2012 Oct 27 → 2012 Oct 29

Publication series

Name	19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management

Conference

Conference	19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management
Country/Territory	China
City	Changsha
Period	12/10/27 → 12/10/29

Keywords

Genetic algorithms
Possibility programming
Recourse cost
Vehicle routing

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

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

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). (19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management). 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 (19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management).

Research output: Chapter in Book/Report/Conference proceeding › Conference 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. 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, China, 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. (19th International Conference on Industrial Engineering and Engineering Management: Engineering Economics Management). doi: 10.1007/978-3-642-38442-4_96

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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.",

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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.

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Genetic algorithms for vehicle routing problem with recourse cost model

Abstract

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Keywords

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