Using Genetic Algorithms to Solve Placement Sequencing Problems and Feeder Arrangement Problems for Turret-type Insertion Machines
碩士 === 國立臺灣大學 === 工業工程學研究所 === 92 === In this thesis, we focus on the insertion sequence problem and the feeder arrangement problem for turret-type insertion machine. One model of heuristic algorithm and three model of genetic algorithm has been display. We compared the performance of these four mod...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/16034806914694595155 |
| Summary: | 碩士 === 國立臺灣大學 === 工業工程學研究所 === 92 === In this thesis, we focus on the insertion sequence problem and the feeder arrangement problem for turret-type insertion machine. One model of heuristic algorithm and three model of genetic algorithm has been display. We compared the performance of these four models on dealing with the insertion sequence problem and the feeder arrangement problem. The 2-section heuristic model is to arrange the feeder arrangement by greedy algorithm, then deciding the insertion sequence by nearest neighbor algorithm. The 2-stage genetic algorithm model is to arrange the insertion sequence and feeder arrangement separately with different fitness function. The mutual freezing genetic algorithm model is to freeze one of the insertion sequence chromosome and the feeder arrangement chromosome, and using just one chromosome to evaluate. But calculate the fitness function by both two chromosomes. The synchronizing genetic algorithm model is to evaluate the insertion chromosome and the feeder arrangement chromosome in the same time. The test data including a benchmark problem obtained from former research, and the others are developed by us to test the performance of these four model. The result shows that the mutual freezing genetic algorithm model can decrease the bottleneck of printed circuit board assembly more than the others.
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