An Application of Ant Colony Optimization to Production Scheduling

• Main Authors: Hung-Chun Hsiung, 熊鴻鈞
• Other Authors: Miao-Tsong Lin
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/96597249112390411456

碩士 === 國立暨南國際大學 === 資訊管理學系 === 91 === In this study, we consider an operations scheduling problem of minimizing total weighted completion time of a given set of jobs or orders under release date constraints. The objective under study is one of the indicators concerning customer satisfaction. Because this problem is already known to be computationally challenging, we circumvent to derive approximate solutions in reasonable time. The approach we adopt in this study is ant colony optimization (ACO), which is a meta-heuristic based upon a nature metaphor concerning the collaboration and knowledge-sharing mechanism exhibited in ant colonies during their food-seeking process. To nicely adapt this approach to resolving the scheduling problem, we propose several specific features that are new to the ACO research. Statistics from our computational experiments evince that the ACO approach equipped with our newly developed features can solve the problem to a certain scale by producing schedules with minor errors.