Abstract
This paper deals with a multi-machine supply chain system operating under just-in- time delivery policy with fuzzy demands. For this purpose, the system is modeled as a fuzzy linear programming problem. In JIT delivery policy, kanban has the role of a transporter. By the solution of the related fuzzy linear programming problem, the number of kanbans is determined optimally. Fuzzy demands method enables one to minimize inventory costs under uncertain demand fluctuations. Copyright © 2007 IFAC
Highlights
In fuzzy decision making problems, the concept of maximizing decision was proposed by several authors (Bellman et al, 1970)
In the work of Husseini (Husseini et al, 2006) a just in time (JIT) based production system composed of I machines, serially connected to produce a single final product is considered
When the part is used for the production, the withdrawal kanban attached to the part is removed and used for the withdrawal of the part to the inventory point
Summary
In fuzzy decision making problems, the concept of maximizing decision was proposed by several authors (Bellman et al, 1970). Tanaka and Asai (Tanaka et al, 1984a) proposed a formulation of fuzzy linear programming with fuzzy constraints and gave a method for its solution which bases on inequality relations between fuzzy numbers. Shaocheng (Shaocheng 1994) considered the fuzzy linear programming problem with fuzzy constraints and defuzificated it by first determining an upper bound for the objective function. Further he solved the soobtained crisp problem by the fuzzy decisive set method introduced by Sakawa and Yana (Sakawa et al.,1985). This is a problem of finding a point which satisfies the constraints and the goal with the maximum degree The idea of this approach is due to Bellman and Zadeh.
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