Particle swarm optimization algorithm based approach to solve Theory of constraint product mix problem

In the recent years, theory of constraint (TOC) has been applied as an effective management tool to solve decision making problems by focusing on the bottleneck and maximizing firm profit. The product mix problem is a major problem and relates to application of TOC in manufacturing enterprises. Product mix problem includes the determination of quantity and identity of products to produce. There are various approaches to solve Product mix problems. However, we can divide these approaches to two divisions as heuristic and meta-heuristic solution methods. Heuristic approaches applied to this problem include traditional TOC by Goldratt and revised TOC, an improved algorithm and etc. meta-heuristic algorithms have been applied extensively in literature such as tabu-search, hybrid Tabu Search and simulated annealing, and Psycho-Clonal algorithm. In this paper a proposed particle swarm optimization (PSO) algorithm is applied to solve the product mix optimization problem. Also, the results obtained from the proposed PSO are compared with the results of other approaches.