Using GA and CTPN for Modeling the Optimization-based Schedule Generator of a Generic Production Scheduling System

• Main Authors: Chien-Hung, Chen, 陳建宏
• Other Authors: Chen-Fu, Chien
• Format: Others
• Language: en_US
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/45720786805823606941

碩士 === 國立清華大學 === 工業工程與工程管理學系 === 91 === In this study, considering the complex problem nature in practical high-tech manufacturing environment from the viewpoints of both theoretical approaches and on-line implementation, a managerial framework in a generic production scheduling (GPS) system from which the generalized unrelated parallel machine scheduling problem (GUPMSP) arises was proposed. GUPMSP is characterized by the following characteristics: unrelated parallel machine environment, dynamic job arrival, non-preemption, inseparable sequence-dependent setup time, multiple resources requirement, general precedence constraint, and job re-circulation. We proposed the optimization-based schedule generator (OptSG) for the approximation of GUPMSP. Separation of model structure and model configuration in OptSG contributes to the structural independence, which makes OptSG robust and convenient in analysis and problem solving of GUPMSP in real settings with changing properties. Meanwhile, we proposed a mixed-integer-linear-programming (MILP) model for the optimization of GUPMSP. This MILP model was developed as a benchmark to estimate the validity of OptSG. Inseparable sequence-dependent setup time and multiple resources requirement that have not been addressed simultaneously in the literature were considered in the MILP model. Finally, we conducted several experiments to compare the solutions of MILP model, OptSG, and dispatching rule-based heuristics (DRBH). The results validated the practical viability of this study.