The IUP Journal of Computer Sciences
Nature-Inspired Harmony Search Algorithm: Latest Developments and Variants
Article Details
| Pub. Date | : Jan, 2024 |
|---|---|
| Product Name | : The IUP Journal of Computer Sciences |
| Product Type | : Article |
| Product Code | : IJCS010124 |
| Author Name | : Abhilasha Nakra and Manoj Duhan |
| Availability | : YES |
| Subject/Domain | : Management |
| Download Format | : PDF Format |
| No. of Pages | : 22 |
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Abstract
Metaheuristic optimization algorithms involve various mathematical techniques inspired from nature and various day-to-day activities. These techniques provide the best solution at minimum cost and error along with maximum profit and utility. They can solve many tough optimization problems where conventional computing techniques do not work. Harmony search algorithm (HSA) is one such relatively recent technique. It is derived from the theory to obtain perfect harmony in music. It can handle diversification and intensification, which makes it a highly efficient metaheuristic algorithm. The paper reviews the latest developments and variants of the algorithm in HSA. It provides insights into the algorithm's applications to help the readers understand it and apply the knowledge obtained in further work.
Introduction
Optimization algorithms are used to find the optimal solutions to problems. It is used in business activities, engineering design, industries, Internet routing, etc. (Yuan et al., 2013). Optimization algorithms are classified into three types on the basis of their nature: deterministic algorithm, stochastic algorithm and hybrid algorithm. Deterministic algorithm follows strict procedure. For example, climbing a hill is a deterministic algorithm as the same path will always be followed from the same starting point. Stochastic algorithm follows random procedure and uses pseudorandom numbers, but the final result will not have much difference. Genetic algorithm is an example of stochastic algorithm. The last one, hybrid algorithm is a combination of stochastic
Keywords
Harmony search algorithm (HRA), Backpropagation (BP), Harmony memory size (HMS), Self adaptive harmony search algorithm (SHSA), Pitch adjustment rate (PAR), Harmony memory considering rate (HMCR), Discrete regularization (DR), Digital versatile disc (DVD), Rapidly adaptive collision backoff (RACB)
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