A Simulated Annealing Approach for Product Mix Decisions

The identification and determination of products and their quantities, according to available resources, is an important matter in manufacturing plants, the answer to which is achieved by referring to objectives. This problem is often called the "product mix" decision, which is one of the applications of the Theory of Constraints (TOC). As the number of resources and products in the "product mix" decision, increase, solving the problem becomes much more complex. Therefore, optimization methods are limited to small-scale problem instances and heuristic methods are introduced for large scale problems. In this research study, while reviewing previous related works, Simulated Annealing (SA) is used to solve the product mix problem. Furthermore, the effect of parameter changes on accuracy and computing time is investigated. The results of SA, in comparison with other heuristic results, show that the efficiency of SA in solving product mix problems is greater than other meta-heuristic methods.