Abstract
Harmony search is an emerging meta-heuristic optimization algorithm inspired from music improvisation processes, and able to solve different optimization problems. In the previous studies harmony search is improved by information of the best solution. This increases speed of coverage to the solution but chance of immature coverage to the local optimum increases by this way. Thus, this study uses information from the p of the best solutions to accelerate coverage to optimal solution while avoiding immature coverage. Simulation results show the proposed approach applied for different numerical optimization problems has better performance than previous approaches.
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Acknowledgments
This work has been supported by the Science Fund of the MOSTI–Ministry of Science, Technology and Innovation (Malaysia; Grant code: 01-01-02-SF1104).
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Maroosi, A., Muniyandi, R.C. (2016). Improved Convergence Behavior by Using Best Solutions to Enhance Harmony Search Algorithm. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_74
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DOI: https://doi.org/10.1007/978-981-10-0448-3_74
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