Reverse geometric programming with fuzzy coefficient and its application in chemical industry production cost analysis

In this text, we discuss fuzzy geometric programming generalized as a solution to a problem in a negative coefficient case, and study this programming in the application in the cost analysis. We consider production cost, profit and its net cost in a chemical plant to be an extended polynomial concerning temperature, pressure and weight proportion. Because the polynomial coefficient undulate within the scope, its function value may swing within a belt district, therefore we find out a fuzzy optimal solution by using fuzzy reverse geometric programming, and proceed to the cost analysis. This method is useful by the proof of numerical examples.