An opposition learning and spiral modelling based arithmetic optimization algorithm for global continuous optimization problems

Yang, Yang; Gao, Yuchao; Tan, Shuang; Zhao, Shangrui; Wu, Jinran; Gao, Shangce; Zhang, Tengfei; Tian, Yu-Chu; Wang, You‐Gan

doi:10.1016/j.engappai.2022.104981

Cited by 31 publications

(7 citation statements)

References 37 publications

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“…The 3-bar truss design (3BTD) is a prominent problem in the field of civil engineering, involving the manipulation of two parameters to attain the minimum weight when designing a truss 52 . Figure 26 visually represents the layout of this problem.…”

Section: Egto For Engineering Design Problemsmentioning

confidence: 99%

Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design

Hassan,

Kamel,

Mohamed

2024

Sci Rep

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This study presents an advanced metaheuristic approach termed the Enhanced Gorilla Troops Optimizer (EGTO), which builds upon the Marine Predators Algorithm (MPA) to enhance the search capabilities of the Gorilla Troops Optimizer (GTO). Like numerous other metaheuristic algorithms, the GTO encounters difficulties in preserving convergence accuracy and stability, notably when tackling intricate and adaptable optimization problems, especially when compared to more advanced optimization techniques. Addressing these challenges and aiming for improved performance, this paper proposes the EGTO, integrating high and low-velocity ratios inspired by the MPA. The EGTO technique effectively balances exploration and exploitation phases, achieving impressive results by utilizing fewer parameters and operations. Evaluation on a diverse array of benchmark functions, comprising 23 established functions and ten complex ones from the CEC2019 benchmark, highlights its performance. Comparative analysis against established optimization techniques reveals EGTO's superiority, consistently outperforming its counterparts such as tuna swarm optimization, grey wolf optimizer, gradient based optimizer, artificial rabbits optimization algorithm, pelican optimization algorithm, Runge Kutta optimization algorithm (RUN), and original GTO algorithms across various test functions. Furthermore, EGTO's efficacy extends to addressing seven challenging engineering design problems, encompassing three-bar truss design, compression spring design, pressure vessel design, cantilever beam design, welded beam design, speed reducer design, and gear train design. The results showcase EGTO's robust convergence rate, its adeptness in locating local/global optima, and its supremacy over alternative methodologies explored.

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Section: Egto For Engineering Design Problemsmentioning

confidence: 99%

Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design

Hassan,

Kamel,

Mohamed

2024

Sci Rep

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“…In 2023, the termite life cycle optimizer (TLCO) was proposed by [55] and operates based on the life cycle of a termite colony in nature. Furthermore, efforts are being made to improve the existing algorithms, and random walk grey wolf Optimizer (In 2019) [56], improved Harris Hawks optimization (In 2020) [57], an improved firefly algorithm with dynamic self-adaptive adjustment (In 2021) [58], a hybrid of opposition learning and spiral modelling based arithmetic optimization algorithm (AOA), called OSAOA (In 2022) [59], a modified version of the seahorse optimization algorithm integrated with chaotic maps (CSHO) (In 2023) [60], and a quasi-opposition based learning and Q-learning based ma- portance in the eastern Pacific Ocean [62]. These fish are 1.5m long and are the largest members of their family.…”

Section: Related Workmentioning

confidence: 99%

Humboldt Squid Optimization Algorithm (HSOA): A Novel Nature-Inspired Technique for Solving Optimization Problems

Anaraki,

Farzin

2023

IEEE Access

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This study presents a new natural-based algorithm called the Humboldt squid optimization algorithm (HSOA). HSOA is inspired by Humboldt squids hunting, moving, and mating behavior. The HSOA search procedure involves an attack on fish schools, a fish's escape, a successful attack, an attack of bigger squids on smaller ones, and mating, which is the inspiration for creating an algorithm to address existing issues. In HSOA, half of the best populations are Humboldt squid, and the rest are school fish. Individuals connect with each other and cooperate to achieve the optimal response. HSOA is versatile and applicable to mathematical and engineering problems. Solving eighty-four benchmark function problems (twenty-three classic functions, twenty-nine CEC-BC-2017 with 10, 30, 50, and 100 dimensions, ten CEC-C06 2019, ten CEC2020 with 5, 10, 15, and 20 dimensions, and twelve CEC2022 with 10 and 20 dimensions) and twenty-four engineering problems (six CEC2006 and eighteen CEC2011) shows that our proposed algorithm provides proper and acceptable answers to nine algorithms, including well-known (PSO, DE, WOA), recent (AVOA, RW_GWO, HHO and GBO), and state-of-the-art algorithms (LSHADE and EBOwithCMAR). Friedman's rank from HSOA for one hundred and eight problems was 16.45% and 7.45% lower than LSHADE and EBOwithCMAR. Thus, HSOA has the potential to solve various complex problems in the sciences and engineering fields.

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“…The AOA improves the dispersion of solution, and overcomes premature convergence ability, and realizes the global explore optimization and local optimization ability. Its optimization process is composed of the several steps, such as initialization, exploration and development [28]. Figure 4 shows model of updating the position of math operators in AOA toward the optimum area.…”

Section: Arithmetic Optimization Algorithm (Aoa)mentioning

confidence: 99%

Intelligent processing of electromagnetic data using detrended and identification

Zhang,

Li,

Liu

et al. 2023

Mach. Learn.: Sci. Technol.

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The application of the electromagnetic method has accelerated due to the demand for the development of mineral resource, however the strong electromagnetic interference seriously lowers the data quality, resolution and detect effect. To suppress the electromagnetic interference, this paper proposes an intelligent processing method based on detrended and identification, and applies for wide field electromagnetic method (WFEM) data. First, we combined the improved intrinsic time scale decomposition (IITD) and detrended fluctuation analysis (DFA) algorithm for removing the trend noise. Then, we extracted the time domain characteristics of the WFEM data after removing the trend noise. Next, the arithmetic optimization algorithm (AOA) was utilized to search for the optimal smoothing factor of the probabilistic neural network (PNN) algorithm, which realized to intelligently identify the noise data and WFEM effective data. Finally, The Fourier transform was performed to extract the spectrum amplitude of the effective frequency points from the reconstructed WFEM data, and the electric field curve was obtained. In these studies and applications, the fuzzy c-mean (FCM) and PNN algorithm are contrasted. The proposed method indicated that the trend noise can be adaptively extracted and eliminated, the abnormal waveform or noise interference can be intelligently identified, the reconstructed WFEM data can effectively recover the pseudo-random signal waveform, and the shape of electric field curves were more stable. Simulation experiments and measured applications has verified that the proposed method can provide technical support for deep underground exploration.

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An opposition learning and spiral modelling based arithmetic optimization algorithm for global continuous optimization problems

Cited by 31 publications

References 37 publications

Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design

Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design

Humboldt Squid Optimization Algorithm (HSOA): A Novel Nature-Inspired Technique for Solving Optimization Problems

Intelligent processing of electromagnetic data using detrended and identification

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