The TOC-Based Algorithm for Solving Multiple Constraint Resources

Abstract

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.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 50 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.