With a comprehensive consideration of multiple product types, past-sequence-dependent （ p-s-d ） setup times, and deterioration effects constraints in processes of wafer fabrication systems, a novel scheduling model ...With a comprehensive consideration of multiple product types, past-sequence-dependent （ p-s-d ） setup times, and deterioration effects constraints in processes of wafer fabrication systems, a novel scheduling model of multiple orders per job（MOJ） on identical parallel machines was developed and an immune genetic algorithm（IGA） was applied to solving the scheduling problem. A scheduling problem domain was described. A non-linear mathematical programming model was also set up with an objective function of minimizing total weighted earliness-tardlness penalties of the system. On the basis of the mathematical model, IGA was put forward. Based on the genetic algorithm （GA）, the proposed algorithm （IGA） can generate feasible solutions and ensure the diversity of antibodies. In the process of immunization programming, to guarantee the algorithm＇s convergence performance, the modified rule of apparent tardiness cost with setups （ATCS） was presented. Finally, simulation experiments were designed, and the results indicated that the algorithm had good adaptability when the values of the constraints＇ characteristic parameters were changed and it verified the validity of the algorithm.展开更多
基金National Natural Science Foundations of China(No.61273035,No.71071115)
文摘With a comprehensive consideration of multiple product types, past-sequence-dependent （ p-s-d ） setup times, and deterioration effects constraints in processes of wafer fabrication systems, a novel scheduling model of multiple orders per job（MOJ） on identical parallel machines was developed and an immune genetic algorithm（IGA） was applied to solving the scheduling problem. A scheduling problem domain was described. A non-linear mathematical programming model was also set up with an objective function of minimizing total weighted earliness-tardlness penalties of the system. On the basis of the mathematical model, IGA was put forward. Based on the genetic algorithm （GA）, the proposed algorithm （IGA） can generate feasible solutions and ensure the diversity of antibodies. In the process of immunization programming, to guarantee the algorithm＇s convergence performance, the modified rule of apparent tardiness cost with setups （ATCS） was presented. Finally, simulation experiments were designed, and the results indicated that the algorithm had good adaptability when the values of the constraints＇ characteristic parameters were changed and it verified the validity of the algorithm.
