An Evolutionary Algorithm for a Single-Item Resource-Constrained Aggregate Production Planning Problem

This paper presents a special design of an evolutionary algorithm based on a genetic algorithm (GA) for solving a generalized model of a single-item resource-constrained aggregate production planning (APP) problem. We linearize a linear mixed-integer model of APP. Due to its NP-hardness one, we develop the proposed GA with effective operators for solving the above model with an integer representation. This model is optimally solved and validated in small-sized problems by an optimization software package, in which the obtained results are compared with the GA results. The results imply the efficiency of the proposed GA achieving to near optimal solutions within a reasonably computational time.