Solving Burn-In Oven Assignment Problem by Genetic Algorithms Combined with Other Heuristic Algorithms

• Main Authors: Szu-Hsien Lu, 呂思賢
• Other Authors: An-Pin Chen
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/47855120209879239724

碩士 === 國立交通大學 === 資訊管理所 === 88 === Burn-in is usually the first and critical process in IC testing. Because of the concern of batch processing property of burn-in ovens and the number of burn-in boards, it''s not only a sequencing but also an assignment problem while scheduling. Although it is affordable for people to schedule when there are only a few jobs and ovens, it is not efficient by people scheduling when jobs and ovens amounts grow larger. Two Burn-In problem models are developed for dealing with different situations and solved by using genetic algorithms. Current studies are shown that general genetic algorithms can not give efficient solutions for these two models because of their integer programming nature with a lot of constraints. In this study, six heuristic algorithms are developed in this research for providing genetic algorithms with better initial solutions. Experiments conclude that the searching processes by using genetic algorithms actually benefit from these high quality starting points. Data of 76 days were collected from an IC testing company for simulation to show the effectiveness of the proposed methods. The results are also compared with those obtained by using integer programming and typical genetic algorithms.