Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications DOI Creative Commons
Shuxin Wang, Yingcai Zheng, Li Cao

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 302 - 302

Published: May 9, 2025

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome drawbacks of (ED) in complex optimization tasks. particular, it aims tackle problems slow convergence and low precision. To enhance algorithm’s ability break free from local optima, lens imaging reverse learning approach incorporated. This creates solutions by utilizing concepts optical imaging. As result, expands search range boosts probability finding superior beyond optima. Moreover, an environmental sensitivity-driven adaptive inertial weight developed. dynamically modifies equilibrium between global exploration, which enables for new promising areas solution space, development, centered on refining close currently best-found areas. evaluate efficacy CAED, 23 benchmark functions CEC2005 are chosen testing. The performance CAED contrasted with that nine other algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf (GWO), Antlion (AOA). Experimental findings show unimodal functions, standard deviation almost 0, reflects its high accuracy stability. case multimodal optimal value obtained notably better than those further emphasizing outstanding performance. also applied engineering challenges, like design cantilever beams three-bar trusses. For beam problem, achieved 13.3925, merely 0.0098. truss 259.805047, extremely small 1.11 × 10−7. These results much traditional ED comparative algorithms. Overall, through coordinated implementation multiple strategies, exhibits precision, strong robustness, rapid when searching spaces. such, offers efficient solving various problems.

Language: Английский

Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications DOI Creative Commons
Shuxin Wang, Yingcai Zheng, Li Cao

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 302 - 302

Published: May 9, 2025

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome drawbacks of (ED) in complex optimization tasks. particular, it aims tackle problems slow convergence and low precision. To enhance algorithm’s ability break free from local optima, lens imaging reverse learning approach incorporated. This creates solutions by utilizing concepts optical imaging. As result, expands search range boosts probability finding superior beyond optima. Moreover, an environmental sensitivity-driven adaptive inertial weight developed. dynamically modifies equilibrium between global exploration, which enables for new promising areas solution space, development, centered on refining close currently best-found areas. evaluate efficacy CAED, 23 benchmark functions CEC2005 are chosen testing. The performance CAED contrasted with that nine other algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf (GWO), Antlion (AOA). Experimental findings show unimodal functions, standard deviation almost 0, reflects its high accuracy stability. case multimodal optimal value obtained notably better than those further emphasizing outstanding performance. also applied engineering challenges, like design cantilever beams three-bar trusses. For beam problem, achieved 13.3925, merely 0.0098. truss 259.805047, extremely small 1.11 × 10−7. These results much traditional ED comparative algorithms. Overall, through coordinated implementation multiple strategies, exhibits precision, strong robustness, rapid when searching spaces. such, offers efficient solving various problems.

Language: Английский

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