Difference priority algorithm in semiconductor scheduling problems

The semiconductor industry is one kind of capital intense industry. To establish a new professional testing company, the budget for machines is almost 90% of the whole company´s expense, and it can be amortized within 5 years only. Thus, how to improve the efficiency and effectiveness of the testing procedure is one of the most important issues for a semiconductor testing company. In this paper, the algorithm MDP-GA is proposed which is a hybrid algorithm of the difference-priority and genetic algorithms (GA). It emphasizes on accelerating the converging process and improves quality of solution obtained. The converging process can be completed within a short time, and the solution will not converge to a local optimized solution. In order to investigate the performance of the MDP-GA, some experiments under the best condition and three different cases are designed for simulation. The numerical results are compared with results from GATS (the hybrid algorithms of GA with Tabu search). From the outputs of the experiments by the MDP-GA and the GATS, the average completion time of the MDP-GA outperforms the GATS. On the best condition, the production rate can raise up to 270%~1000% by the MDP-GA.