Paper Title:
Transportation Chance Constrained Model with Fuzzy Parameters
  Abstract

This paper presents how credibility theory and chance constrained optimization method can be efficiently applied for modelling and solving transportation problem in fuzzy environment. Since the proposed transportation model includes fuzzy variable coefficients defined through possibility distributions with infinite supports, it is infinite-dimensional optimization problem. Therefore, we can not solve directly it by conventional optimization algorithms. To overcome this difficulty, we will discuss the approximation of the fuzzy transportation chance constrained problem in this paper, and design a heuristic algorithm, which combines approximation method (AM), neural network (NN) and genetic algorithm (GA) algorithm to solve this transportation chance constrained model. Finally, we present one numerical example to show the feasibility and effectiveness of the proposed method.

  Info
Periodical
Chapter
Chapter 8: Other Applications
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
1193-1200
DOI
10.4028/www.scientific.net/AMM.135-136.1193
Citation
G. Q. Yuan, M. Q. Meng, C. P. Li, "Transportation Chance Constrained Model with Fuzzy Parameters", Applied Mechanics and Materials, Vols. 135-136, pp. 1193-1200, 2012
Online since
October 2011
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$32.00
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