Research on the Vehicle Routing Problem with Fuzzy Demands

Lian Xue; Xiao Xia Dai

doi:10.4028/www.scientific.net/AMR.186.570

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 186Research on the Vehicle Routing Problem with Fuzzy...

Research on the Vehicle Routing Problem with Fuzzy Demands

Abstract:

In this paper, the vehicle routing problem with fuzzy demands is considered, and a fuzzy chance constrained programming mathematical model is established based on fuzzy possibility theory. Then fuzzy simulation and differential evolution algorithm are integrated to design a hybrid intelligent algorithm to solve the fuzzy vehicle routing model. Moreover, under the target that the total driving distance of vehicles is the shortest, the influence of the decision-maker’s preference on the final objective of the problem is discussed using the method of stochastic simulation, and the rational range of the preference number is obtained.

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Periodical:

Advanced Materials Research (Volume 186)

Pages:

570-575

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.186.570

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Online since:

January 2011

Authors:

Lian Xue, Xiao Xia Dai

Keywords:

Differential Evolution (DE), Fuzzy Possibility, Fuzzy Simulation, Optimization, Vehicle Routing Problem (VRP)

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References

[1] Dantzing G, Ramser J: The truck dispatching problem, Management Science, Vol. 10(1959), p.80.

Google Scholar

[2] Teodorovic D: The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain. Fuzzy Sets and Systems, Vol. 82(1996), p.307.

DOI: 10.1016/0165-0114(95)00276-6

Google Scholar

[3] Zheng Y, Liu B: Fuzzy vehicle routing model with credibility measure and its hybrid untelligent algorithm. Applied Mathematics and Computation, Vol. 176(2006), p.673.

DOI: 10.1016/j.amc.2005.10.013

Google Scholar

[4] Cheng R, Gen M: Vehicle routing problem with fuzzy due-time by generic algorithm. Japanese Journal of Fuzzy Theory and Systems, Vol. 7(1995), p.1050.

Google Scholar

[5] Storn R: Differential evolution design of an IIR-filter. Proceedings IEEE Conference Evolutionary Computation, 1996, p.268.

DOI: 10.1109/icec.1996.542373

Google Scholar

[6] DEA Home page on http: /www. icsi, berkeley. edu/~stirn/code. html.

Google Scholar

[7] Liu B: Uncertain theory: an introduce to its axiomatic foundations (Springer, Berlin 2004).

Google Scholar