Transportation Chance Constrained Model with Fuzzy Parameters

Abstract:

Article Preview

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:

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 et al., "Transportation Chance Constrained Model with Fuzzy Parameters", Applied Mechanics and Materials, Vols. 135-136, pp. 1193-1200, 2012

Online since:

October 2011

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.