The TOC-Based Algorithm for Solving Multiple Constraint Resources

The theory of constraints (TOC) emphasizes the exploitation of resource constraints in order to increase the product throughput of an organization. The product-mix decision is one application of the five steps in the TOC. This paper considers an integrated heuristic model comprising the analytic hierarchy process (AHP) and the TOC in a decision model in which priority of product and resource center optimizes the product throughput in a multiple constraint resource environment. An AHP component allows the decision maker to incorporate tangible and intangible criteria into the decision-making process and use the priority rankings of the AHP to represent a measure of value in the TOC model. The TOC identifies the constraints and the product ranking of the AHP maximizes the product throughput in a multiple constraint resource environment. The methodology incorporates sensitivity analysis to provide the decision maker with additional information regarding the robustness of the model so that he or she can make a better decision. The model compares three alternatives: the standard TOC, Integer Linear Programming (ILP), and our own solution. The numerical result shows that the proposed approach is superior to TOC and to ILP analysis and provides a measure of the model's performance.