Abstract: With a comprehensive consideration of the characteristics of multiple product types, the past-sequence-dependent (p-s-d) setup times and the deterioration effects constraints in processes of wafer fabrication, a scheduling model of multiple orders per job(MOJ) in a single machine is developed and a modified genetic algorithm-ant colony optimization(MGA-ACO) algorithm is applied to solve the scheduling problem. Firstly, a scheduling problem domain is described. Mathematical programming models are also set up with an objective function of minimizing total weighted earliness-tardiness penalties of the system. On the basis of the descriptions, the decision-making variables are separated and a MGA-ACO algorithm adopting two-level encoding mechanism is put forward. Genetic algorithm is introduced into the process of dynamic and adaptive ant colony iterations. To guarantee the algorithm convergence performance, the modified rules of apparent tardiness cost with setups(ATCS) is developed. Finally, the simulation experiments are designed, and the results indicate that the developed algorithm is valid and feasible.

Key words: multiple product types, p-s-d setup times, deterioration effects, scheduling, MGA-ACO algorithm