Optimizing Production Management Model Using Fuzzy Linear Programming

Manufacturing firm focuses on maximizing the profit by satisfying the customer demands with respect to quantity, quality, cost etc. To achieve the goal they give importance to optimum utilization of available resources. Information available in real life system is of vague, imprecise and uncertain nature. The impreciseness and uncertainty aspects are handled using fuzzy sets to obtain optimal solution. In practice, choosing membership thresholds arbitrarily may result in an infeasible optimization problem. Even though we can adjust minimum satisfaction degree to get fuzzy efficient solution it sometimes makes the process of interaction more complicated. The present paper demonstrates how vagueness and imprecision in the objective function values can be quantified by membership functions in a Fuzzy multi objective frame work. It focuses on optimizing production management model using real world data of a packaging industry. Production model intends to determine the sales value of each product produced in order to achieve objectives (i.e.) maximize profit, minimize wastes etc. Multiple objective functions in the linear programming model are handled by fuzziness in the parameters. Fuzzy linear programming approach exhibits greater computational efficiency by employing the linear membership functions to represent fuzzy numbers.