A Self-Adaptive Dynamic Scheduling Methodology

• Main Authors: Yu-Jen Chang, 張育仁
• Other Authors: Ching-En Lee
• Format: Others
• Language: zh-TW
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/66420940094096685349

博士 === 國立交通大學 === 工業工程與管理系 === 88 === Scheduling plays an important role in a complex and dynamic manufacturing environment. To enhance scheduling performance, a systematic approach that effectively integrates order release and dispatching decisions is necessary. In addition, to incorporate with planners'' or shop supervisors'' knowledge and experiences, vague information and events of a manufacturing system can be efficiently managed. Besides, operation sequence of bottleneck is the core of scheduling activities and the primary key of improving system performance. In this study, a self-adaptive dynamic scheduling methodology focusing on the above intentioned characteristics is proposed. This methodology uses a modified Tabu search method to optimize the operation sequence of bottleneck. Order release and dispatching decisions are made, thereafter, according to scheduling information of bottleneck. Fuzzy theory incorporated with genetic algorithm is applied to construct a knowledge base with planners'' knowledge and experiences which can improve the proceeding shop''s scheduling decisions. Although the proposed self-adaptive dynamic scheduling methodology still has some unsolved problems, simulation results show that both knowledge base and bottleneck schedule can be used to effectively improve performance of manufacturing systems.