MODIFIED HARMONY SEARCH OPTIMIZATION METHOD WITH PARAMETER FREE PENALTY FUNCTION AND SPIRAL DYNAMICS CLUSTERING
In this final project, the author proposes a newly developed metaheuristic optimization method for solving an optimization problem. This method will combine the optimization method, that is the Modified Harmony Search, a penalty function Parameter Free Penalty, and Spiral Dynamics Clustering. Th...
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| Main Author: | |
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/71804 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In this final project, the author proposes a newly developed metaheuristic
optimization method for solving an optimization problem. This method will
combine the optimization method, that is the Modified Harmony Search, a penalty
function Parameter Free Penalty, and Spiral Dynamics Clustering.
The Modified Harmony Search Method imitates the performance of music harmony
to find the best possible harmony iteratively. Each stage in the Modified Harmony
Search will be explained in this project, as well as how a penalty function such as
the Parameter Free Penalty can help Modified Harmony Search find the feasible
solution and also the Spiral Dynamics Clustering to divide a domain into regions
that might have an optimum solution.
All theories discussed in this project are implemented in the new innovation method
which will be called as PFP-SDC-MHS method using the python language. After
the method had been successfully developed, the PFP-SDC-MHS method is then
used to solve various types of optimization problems. |
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