A combinatorial optimization technique using genetic algorithm :a case study in machine layout problem
Solving Combinatorial Optimization Problem is significant a s it abounds in our daily lives. However, it is impractical to solve combinatorial optimization problems by exploring all the possible solutions due to combinatorial explosion. Genetic Algorithms (GAs) are a powe...
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| Main Author: | |
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| Format: | Final Year Project Report / IMRAD |
| Language: | en en |
| Published: |
Universiti Malaysia Sarawak, UNIMAS
2007
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/6719/1/A%20COMBINATORIAL%20OPTIMIZATION%20TECHNIQUE%20USING%20GENETIC%20ALGORITHM%2C%20A%20CASE%20STUDY%20IN%20MACHINE%20LAYOUT%20PROBLEM%2024%20pgs.pdf http://ir.unimas.my/id/eprint/6719/7/LAU%20SIEW%20YUNG.pdf http://ir.unimas.my/id/eprint/6719/ |
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| Summary: | Solving Combinatorial Optimization Problem is significant a
s it abounds in our daily lives.
However, it is
impractical to solve combinatorial optimization problems by exploring all the
possible solutions
due to combinatorial explosion. Genetic
Algorithms (GAs) are a powerful stochastic search in solving optimization problems.
However, conventional GAs with binary representation approach cannot be used in
solving these kinds of problems. In this study, different crossover and mutation techniques a
re adapted in GAs so that it suits
to combinatorial optimization. In
empirical tests, the combinatorial optimization techniques using GAs are able to
approximating optimization, which had been
justified theoretically in a
simple Machine Layout Problem (MLP).
Several complex cases
of MLP also had been
demonstrated and the results
of different input parameters are
compared. |
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