Decomposition-based classified ant colony optimization algorithm for scheduling semiconductor wafer fabrication system

• Published in: Computers & industrial engineering Vol. 62; no. 1; pp. 141 - 151
• Main Authors: Guo, Chengtao, Zhibin, Jiang, Zhang, Huai, Li, Na
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.02.2012; Pergamon Press Inc
• Subjects: Algorithms; Ant colony optimization; Colonies; Computer simulation; Decomposition; Decomposition-based classified ACO (D-CACO); Optimization; Optimization algorithms; Schedules; Scheduling; Semiconductor wafer fabrication system (SWFS); Semiconductors; Sequential scheduling; Simulation; Studies; Ant colony optimization; Scheduling; Decomposition; Semiconductor wafer fabrication system (SWFS); Decomposition-based classified ACO (D-CACO)
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2011.09.002

► Schedule the semiconductor wafer fabrication system by proposed D-CACO algorithm. ► Divide the large scale scheduling problem into smaller subproblems by decomposition method. ► Schedule every smaller subproblem by classified ACO algorithm. ► The experiment results justified the effectiveness of proposed algorithm. ► Increasing the size of subproblem will improve quality of solution found by the algorithm. Due to its typical features, such as large-scale, multiple re-entrant flows, and hybrid machine types, the semiconductor wafer fabrication system (SWFS) is extremely difficult to schedule. In order to cope with this difficulty, the decomposition-based classified ant colony optimization (D-CACO) method is proposed and analyzed in this paper. The D-CACO method comprises decomposition procedure and classified ant colony optimization algorithm. In the decomposition procedure, a large and complicate scheduling problem is decomposed into several subproblems and these subproblems are scheduled in sequence. The classified ACO algorithm then groups all of the operations of the subproblems and schedules them according to machine type. To test the effect of the method, a set of simulations are conducted on a virtual fab simulation platform. The test results show that the proposed D-CACO algorithm works efficiently in scheduling SWFS.