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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 256428, 11 pages
http://dx.doi.org/10.1155/2015/256428
Research Article

Credibility-Based Biobjective Fuzzy Optimization for Supplier Selection Problem with Disruption

1College of Science, Hebei Agricultural University, Baoding, Hebei 071001, China
2College of Management, Hebei University, Baoding, Hebei 071002, China

Received 14 July 2015; Revised 24 September 2015; Accepted 28 September 2015

Academic Editor: Thomas Hanne

Copyright © 2015 Xuejie Bai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper addresses a supplier selection problem in which a buyer procures multiple products from multiple suppliers under disruption risk. The problem is formulated as a new credibility-based biobjective fuzzy optimization model. In the proposed model, cost, capacity, and demand are characterized by fuzzy variables with known possibility distributions. The objectives of our model are to maximize the total quality of purchased products and minimize the expected total cost. Two credibility constraints are used to guarantee that the chance about the supplier capacity and buyer demand can satisfy the predetermined levels. The main concern in solving the optimization model is to calculate the expected value of the objective function and the credibility in the constraints. When the key parameters are mutually independent triangular fuzzy variables, the expected cost objective and credibility constraints can be transformed into their equivalent forms. Taking advantage of the structural characteristics of the equivalent model, the goal programming method is employed to solve the supplier selection model, which can be solved by conventional optimization method. At last, some numerical experiments have been performed to illustrate the effectiveness of the proposed model and solution strategy.