Optimizing the multiple constrained resources product mix problem using genetic algorithms

The theory of constraints (TOC) is s a management philosophy for maximizing throughput. Since its introduction, many have criticized it as being inefficient when multiple constrained resources exist. The application of the five steps contained in TOC have been criticized by some researchers on the grounds that the application of five steps of TOC to the product mix decision leads to implicit or unrealizable solutions when multiple resource constraints in a plant exist. This paper views TOC as a management philosophy and a genetic algorithm-based TOC procedure is presented for solving combinatorial problems encountered in practice which cannot be solved using linear-integer programming or similar techniques. For smaller size problems, the results of the proposed procedure are compared with results of optimal methods published in the literature. The results are encouraging and therefore support the use of the proposed approach in an industrial setting.