TOC product mix optimization with extending capacity of outsourcing - Part II: Simulation

The theory of constraints (TOC) product mix problems considering outsourcing that involves determination of the quantity and the identification of each product to make or buy is one of the most fundamental decisions in a manufacturing plant. Aiming at the problem model discussed in the part I, an immune algorithm (IA) was introduced to resolve the problem where the original TOC heuristic (TOCh) failed. The algorithm is accomplished by two successive phases. The first is pretreatment phase which reduces the fake restriction from the constraints of TOC product mix optimization problem as much as possible for simplifying the given problem. The second is immune evolutionary phase which uses IA to obtain optimal solution. Especially, some of the TOC philosophy is transferred into heuristic information, and the explicit optimizing process of TOCh is further embedded into IA to form immune response mechanism, which consists of immune recognition, immune learning, and immune memory. The immune mechanism, combining with immune selection mechanism, immune self-adaptive regulation mechanism and vaccination mechanism implemented ensures that the immune evolution always moves forward the direction of optimization in feasible space, which not only improves the searching ability and the adaptability greatly, but also increases the global convergence speed evidently. Simulation results for small or large size product mix problems with the extending capacity of outsourcing show that the IA-based optimal method published in the literature is effective in achieving the optimal or near optimal solution in reasonable times. Therefore, the proposed approach is appropriate for adoption by production planners for the product mix decision with the extending capacity of outsourcing in the manufacturing plant.