Optimizing Production Management Model Using Fuzzy Linear Programming

Abstract

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.