Bayesian Optimization for Weight-based Dispatching of Stocker Systems in a Display Fab
Journal : Korean Society of Industrial and Systems Engineering
Title : Bayesian Optimization for Weight-based Dispatching of Stocker Systems in a Display Fab
Authors : Jonghyeon Chun, Bosung Kim, Min Hong, and Soondo Hong
Abstract : The stocker is a critical material handling system for transporting work-in-process materials in a display fab. Efficient dispatching is particularly challenging in twin-crane system. The cranes share a single track while jobs arrive dynamically. In this study, we consider a weight-based dispatching method that combines multiple dispatching rules. The weight set determines the relative importance of multiple dispatching rules with competing objectives such as job priority and travel time, and its effectiveness varies with system dynamics. Evaluating weight sets requires simulation in stochastic and dynamic systems, which is computationally expensive. We therefore propose a simulation optimization framework to efficiently search the best weight set. Gaussian process-based Bayesian optimization is employed to guide the search under a limited simulation budget. Experimental results show that the relative importance of dispatching rules changes across scenarios. The proposed framework consistently identifies effective weight sets across diverse operating conditions.
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