• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.232-239
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• 2006

This paper is for applying interactive fuzzy linear programming for the problem of product mix planning, which is one of the aggregate planning problem. We developed a modified algorithm, which has two-phase approach for interactive fuzzy linear programming to get a better solution. Adding two-phase method, we expect to obtain not only the highest membership degree, but also a better utilization of each constrained resource.

• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.1-10
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• 2012

Supplier selection is an essential task within the purchasing function of supply chain management because it provides companies with opportunities to reduce various costs and realize stable and reliable production. However, many companies find it difficult to determine which suppliers should be targeted as each of them has varying strengths and weaknesses in performance which require careful screening by the purchaser. Moreover, information required to assess suppliers is not known precisely and typically fuzzy in nature. In this paper, therefore, fuzzy multi-objective linear programming (fuzzy MOLP) is presented under fuzzy goals: cost minimization, service level maximization and purchasing risk. To solve the problem, we introduce an enhanced two-phase approach of fuzzy linear programming for the supplier selection. In formulated problem, Analytical Hierarchy Process (AHP) is used to determine the weights of criteria, and Taguchi Loss Function is employed to quantify purchasing risk. Finally, we provide a set of alternative solution which enables decision maker (DM) to select the best compromise solution based on his/her preference. Numerical experiment is provided to demonstrate our approach.

• 한국안전학회지
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• 제12권1호
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• pp.122-128
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• 1997

A new approach, called "two-phase approach", has been proposed In this study. Using this approach to solve MONLP(multiobjective nonlinear programming problem), the solution process is divied into two phase. In the first phase, the min-operator is used to aggregate the membership degree of fuzzy goals and constraints. In the second phase, the $\gamma$-operator is used to test and find an efficient solution in the sense of nondominated. It has been shown that no matter what the solution of the problem is unique or not, an efficient solution can be always obtained at the second phase. The proposed approach can be applied to industrial safety problem with multiobjective problems. On the basis of proposed approach, an illustrative numerical example is presented.presented.