A novel meta-heuristic algorithm named as the Cell Division Optimizer (CDO) is proposed. The proposed algorithm is inspired by the reproduction methods at the cellular level, which is formulated by the well-known cell division process known as mitosis and meiosis. In the proposed model Meiosis ...
In this paper, Energy Valley Optimizer (EVO) is proposed as a novel metaheuristic algorithm inspired by advanced physics principles regarding stability and different modes of particle decay. Twenty unconstrained mathematical test functions are utilized i
The main contribution of this paper is to propose a novel search method for optimization purposes in which an intelligent procedure is conducted for finding the best optimal values of different optimization problems. The applicability of the proposed method in dealing with difficult optimum design probl...
AO的Matlab代码位于https://www.mathworks.com/matlabcentral/fileexchange/89381-aquila-optimizer-a-meta-heuristic-optimization-algorithm,而Java代码位于https://www.mathworks。 com / matlabcentral / fileexchange / 89386-aquila-optimizer-a-meta-heuristic-optimization-algorithm。
A.H., Aquila Optimizer: A novel meta-heuristic optimization Algorithm, Computers & Industrial Engineering (2021), doi:https://doi.org/10.1016/j.cie.2021.107250 Code available at Researchgate:https://www.researchgate.net/publication/350411564_Matlab_Code_of_Aquila_Optimizer_A_novel_meta-heurist...
Finally, a set of seven real-world engineering problems are used. From the experimental results of AO that compared with well-known meta-heuristic methods, the superiority of the developed AO algorithm is observed. 展开 关键词: Aquila Optimizer (AO) Optimization algorithms Meta-heuristics Real-...
This paper presents a novel population-based meta-heuristic algorithm inspired by the game of tug of war. Utilizing a sport metaphor the algorithm, denoted as Tug of War Optimization (TWO), considers each candidate solution as a team participating in a series of rope pulling competitions. The ...
Optimization methodologies that are based on meta-heuristic procedures could assist power generation policy analysts to achieve the goal of minimizing the generation costs. In this context, the objective of this study is to present a novel approach based on harmony search (HS) algorithm for solving...
This paper presents a novel hybrid meta-heuristic algorithm called HMGSG to solve the optimization problems. In the proposed HMGSG algorithm, a spiral-shaped path for grey wolf optimization (GWO) is used to ensure both the faster convergence rate and diversity. The mutualism phase of symbiotic ...
A more efficient optimization algorithm has always been the pursuit of researchers, but the performance of the current optimization algorithm in some complex test functions is not always satisfactory. In order to solve this problem, a new meta-heuristic optimization algorithm—Football Team Training Al...