ACO-Based Scheduling of Parallel Batch Processing Machines with Incompatible Job Families to Minimize Total Weighted Tardiness

Abstract

This research is motivated by the scheduling problem in the diffusion and oxidation areas of semiconductor wafer fabrication facilities (fabs), where the machines are modeled as Parallel Batch Processing Machines (PBPM). The objective is to minimize the Total Weighted Tardiness (TWT) on PBPM with incompatible lot families and dynamic lot arrivals, with consideration on the sequence-dependent setup times. Since the problem is NP-hard, Ant Colony Optimization (ACO) is used to achieve a satisfactory solution in a reasonable computation time. A number of experiments have been implemented to demonstrate the proposed method. It is shown by the simulation results that the proposed method is superior to the common Apparent Tardiness Cost-Batched Apparent Tardiness Cost (ATC-BATC) rule with smaller TWT and makespan, especially TWT that has been improved by 38.49% on average.KeywordsBatch ProcessorVariable Arrival TimeSingle Batch Processing MachineParallel Batch Processing MachineParallel Batch MachineThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.