Imprecise aggregate production planning decisions using interactive possibilistic linear programming

Abstract

The goal and model inputs when applies any of conventional techniques to APP decisions are generally assumed to be deterministic/crisp, and the major limitation of these techniques is that they do not consider the time value of money for each of operating cost categories. This work presents an interactive possibilistic linear programming (PLP) method for the solving the aggregate production planning (APP) problems with imprecise goal, forecast demand, related capacities and operating costs in uncertain environments. The imprecise APP model designed here attempts to minimize total manufacturing costs with reference to inventory, labor, overtime, subcontracting and backordering levels, machine capacity, warehouse space, and the time value of money for each of the operating cost categories. The proposed PLP method achieves greater computational efficiency by employing the simplified triangular distribution to specify imprecise goal and related coefficients. The analytical results obtained by implementing a real industrial case indicate that the proposed PLP method is practically applicable for solving the practical APP problems in uncertain environments.