A Fuzzy Nonlinear Programming Approach for Optimizing the Performance of a Four-Objective Fluctuation Smoothing Rule in a Wafer Fabrication Factory

Abstract

In theory, a scheduling problem can be formulated as a mathematical programming problem. In practice, dispatching rules are considered to be a more practical method of scheduling. However, the combination of mathematical programming and fuzzy dispatching rule has rarely been discussed in the literature. In this study, a fuzzy nonlinear programming (FNLP) approach is proposed for optimizing the scheduling performance of a four-factor fluctuation smoothing rule in a wafer fabrication factory. The proposed methodology considers the uncertainty in the remaining cycle time of a job and optimizes a fuzzy four-factor fluctuation-smoothing rule to sequence the jobs in front of each machine. The fuzzy four-factor fluctuation-smoothing rule has five adjustable parameters, the optimization of which results in an FNLP problem. The FNLP problem can be converted into an equivalent nonlinear programming (NLP) problem to be solved. The performance of the proposed methodology has been evaluated with a series of production simulation experiments; these experiments provide sufficient evidence to support the advantages of the proposed method over some existing scheduling methods.

Solving a Fully Fuzzy Linear Programming Problem through Compromise Programming

“…Definition 1 (see [20,22]). A fuzzy number̃= ( (1) , (2) , (3) ) is said to be a triangular fuzzy number if its membership function is given bỹ…”

“…Definition 3 (see [23]). Let̃= ( (1) , (2) , (3) ) and̃= ( (1) , (2) , (3) ) be two triangular fuzzy numbers, and then the similarity betweeñand̃can be defined as…”

“…A ranking function is a function R : ( ) → , where ( ) is a set of fuzzy numbers defined on set of real numbers, which maps each fuzzy number into the real line, where a natural order exists. Let̃= ( (1) , (2) , (3) ) be a triangular fuzzy number; then…”

“…Recently fuzzy set theory has been applied in many research regions, since fuzzy set theory is effective to solve the decision-making problems with imprecise data [1][2][3]. Several kinds of the FLP problems have appeared in the literature [4][5][6][7][8][9][10][11][12][13][14][15][16].…”

A new cloud computing method for establishing asymmetric cycle time intervals in a wafer fabrication factory

“…Cycle-time prediction is also related to job scheduling (Sivakumar, 1999;Tsai & Chen, 2013), due-date assignment (Joseph & Sridharan, 2011;Mor et al, 2013), and avail-to-promise (ATP) calculation (Oracle, 2014). With the improvement of prediction accuracy in cycle times, the obstacle of determining the range of a cycle time gradually emerges.…”