Zobrazeno 1 - 10
of 485
pro vyhledávání: '"engineering design problems"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Addressing the imbalance between exploration and exploitation, slow convergence, local optima Traps, and low convergence precision in the Northern Goshawk Optimizer (NGO): Introducing a Multi-Strategy Integrated Northern Goshawk Optimizer (M
Externí odkaz:
https://doaj.org/article/4d85b5f843994a7082b84da6ef77b63a
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract The Marine Predator Algorithm (MPA) has unique advantages as an important branch of population-based algorithms. However, it emerges more disadvantages gradually, such as traps to local optima, insufficient diversity, and premature convergen
Externí odkaz:
https://doaj.org/article/81fe44c3b0664e639602040691fe73c4
Autor:
Aula, Sirwan A. a, Rashid, Tarik A. b, ⁎
Publikováno v:
In Ain Shams Engineering Journal January 2025 16(1)
Publikováno v:
Heliyon, Vol 10, Iss 18, Pp e37819- (2024)
The Snow Ablation Optimizer (SAO) is an advanced optimization algorithm. However, it suffers from slow convergence and a tendency to become trapped in local optima. To address these limitations, we propose an Enhanced Snow Ablation Optimization algor
Externí odkaz:
https://doaj.org/article/56405522138e462ebe3585e6e85cd36a
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract To address the issues of lacking ability, loss of population diversity, and tendency to fall into the local extreme value in the later stage of optimization searching, resulting in slow convergence and lack of exploration ability of the arti
Externí odkaz:
https://doaj.org/article/b21204da70ae421eae5bdf29e68cab3c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-38 (2024)
Abstract Addressing the challenge of efficiently solving multi-objective optimization problems (MOP) and attaining satisfactory optimal solutions has always posed a formidable task. In this paper, based on the chicken swarm optimization algorithm, pr
Externí odkaz:
https://doaj.org/article/2e2a72a6b7294d1982d78b4038519059
Publikováno v:
In Heliyon 30 September 2024 10(18)
Publikováno v:
Ain Shams Engineering Journal, Vol 15, Iss 7, Pp 102797- (2024)
For the problems of Grey wolf optimizer (GWO) easy to fall into local optimum and lack of population diversity, this thesis raises a Grey wolf optimizer combined with an Artificial fish swarm algorithm (AFGWO). First, the search method of grey wolves
Externí odkaz:
https://doaj.org/article/8d3c1f40214e4bfbaeff950aef7ca09c
Autor:
Vanisree Chandran, Prabhujit Mohapatra
Publikováno v:
Heliyon, Vol 10, Iss 10, Pp e30757- (2024)
Over the last few decades, a number of prominent meta-heuristic algorithms have been put forth to address complex optimization problems. However, there is a critical need to enhance these existing meta-heuristics by employing a variety of evolutionar
Externí odkaz:
https://doaj.org/article/3e6d7fcaeab74fffbf5df2e7184a7f04