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Abstract: <br /> <br /> <br /> <br /> <br /> Layouting problems are a common problem in our life. Introducing new item will increase the problem complexity because it will multiply the variation of possible layout in order to optimize space used for all items. &...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/8634 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Abstract: <br />
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Layouting problems are a common problem in our life. Introducing new item will increase the problem complexity because it will multiply the variation of possible layout in order to optimize space used for all items. <br />
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This thesis implements genetic algorithm as a method to solve layouting problems. Genetic algorithm operators used in this thesis are roulette wheel selection method, single-point crossover method, and binary mutation method. This thesis proves that genetic algorithm implementation used to solve layouting problems capable to archieve a 84% of solution quality for heterogen item cases and 100% for homogen item cases. <br />
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