Overview of metaheuristic: classification of population and trajectory
Algorithms are used to find the solutions through the computer program. Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. The me...
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| Main Author: | |
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| Format: | Monograph |
| Language: | en |
| Published: |
Universiti Teknologi MARA
2010
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/121761/1/121761.PDF https://ir.uitm.edu.my/id/eprint/121761/ |
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| Summary: | Algorithms are used to find the solutions through the computer program. Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. The metaheuristic method depends on the structure of the search space to find the solution efficiently without using problem-specific knowledge. There are five classifications in the metaheuristic method. One of the classifications is population vs. trajectory. In this paper, several algorithm techniques based on population and trajectory characteristics are discussed. The algorithm techniques can be characterized based on the criteria of the operation of the search process. A system that does not have any specific method like the scheduler system can be developed by applying one of the techniques to get the knowledge that can be used to produce an optimum solution. |
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