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Gravitational evaluation algorithm for global optimization problem | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 32، دوره 13، شماره 2، مهر 2022، صفحه 345-359 اصل مقاله (958.8 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6248 | ||
| نویسندگان | ||
| Hasanain Jalil Neamah* 1، 2، 3؛ Ali M. Almobarqaa4؛ Zainab Ali Abdulhusien1 | ||
| 1Faculty of Management, University of Warsaw, Poland | ||
| 2University of Information Technology and Communications, Baghdad, Iraq | ||
| 3Acharya Nagarjuna University, Guntur, India | ||
| 4Consultor of Development and Social Justice, Iraqi Parliament Council, Baghdad, Iraq | ||
| تاریخ دریافت: 17 آذر 1400، تاریخ بازنگری: 07 بهمن 1400، تاریخ پذیرش: 21 بهمن 1400 | ||
| چکیده | ||
| This work proposes a new metaheuristic technique that combines Differential evolution (DE) with gravity search in a consistent manner. Swarm intelligence benefits and the concept of tensile strength between two particles are combined to suggest superior meta-heuristic approaches for limitless optimization issues. The goal of this paper is to create a new algorithm that overcomes the shortcomings of the Gravitational search algorithm by leveraging the advantages of the Differential evolution algorithm in expanding search areas, overcoming early convergence problems, and improving the attractive algorithm's ability to converge towards the optimum. The GSA algorithm has been utilized in a search-oriented algorithm, whereas the Differential evolution algorithm is causing a high level of diversification in society, which leads to the establishment of search regions for the GSA algorithm. The effectiveness of the suggested approach was evaluated by solving a collection of 30 Real-Parameter Numerical Optimization problems that were presented at IEEE-CEC 2014. The findings are compared to 5 state-of-the-art unconstrained problem algorithms and 6 state-of-the-art unconstrained problem algorithms. The winner methods were also deduced from the results using the Wilcoxon signed test. | ||
| کلیدواژه‌ها | ||
| gravitational search algorithm؛ global optimization؛ differential evolution؛ hybrid algorithms | ||
| مراجع | ||
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