MULTI-PERIOD PRODUCTION PLANNING UNDER FUZZY CONDITIONS

In the real-world multi-period production/operations management (MP-POM) problems, the parameters must be estimated and they are frequently given by interval estimates. But for most POM models, these interval estimates must be translated into single numbers. This often results in errors and in the loss of a considerable amount of information. The purpose of this paper is to develop, apply, and illustrate a new fuzzy approach using fuzzy numbers to solve the interval MP-POM problem. It consists of employing appropriate fuzzy numbers to represent the interval estimates in the multi-stage decision problems; using the operations of fuzzy numbers combined with dynamic programming to solve the problem; and determining the required minimum/maximum fuzzy number through ranking techniques. To demonstrate the application of this approach, three MP-POM problems with fuzzy costs and/or fuzzy demands are solved. The main advantages of this approach are fuzzy representative solutions for the optimal production schedule and the minimum total cost in terms of interval units rather than single numbers. This enables the production engineers and operations managers to manage the production flexibly and control the costs effectively. A significant original contribution of this research is the development of an effective technique to solve the fuzzy MP-POM problems that have not been addressed thus far. Suggestions for future research include extending the proposed general fuzzy approach to solve large scale multistage fuzzy problems using computers; and to solve problems with fuzzy goals and constraints defined in different spaces.