Hybrid Cuckoo Search-Gorilla Troops Optimizer for Optimal Parameter Estimation in Photovoltaic Modules DOI Creative Commons

Abdelmalek Gacem,

Ridha Kechida, Youcef Bekakra

и другие.

Journal of Engineering Research, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

Bald eagle search algorithm: a comprehensive review with its variants and applications DOI Creative Commons
M.A. El‐Shorbagy, Anas Bouaouda, Hossam A. Nabwey

и другие.

Systems Science & Control Engineering, Год журнала: 2024, Номер 12(1)

Опубликована: Авг. 1, 2024

Bald Eagle Search (BES) is a recent and highly successful swarm-based metaheuristic algorithm inspired by the hunting strategy of bald eagles in capturing prey. With its remarkable ability to balance global local searches during optimization, BES effectively addresses various optimization challenges across diverse domains, yielding nearly optimal results. This paper offers comprehensive review research on BES. Beginning with an introduction BES's natural inspiration conceptual framework, it explores modifications, hybridizations, applications domains. Then, critical evaluation performance provided, offering update effectiveness compared recently published algorithms. Furthermore, presents meta-analysis developments outlines potential future directions. As swarm-inspired algorithms become increasingly important tackling complex problems, this study valuable resource for researchers aiming understand algorithms, mainly focusing comprehensively. It investigates evolution, exploring solving intricate fields.

Язык: Английский

Процитировано

9

Advancing Engineering Solutions with Protozoa-Based Differential Evolution: A Hybrid Optimization Approach DOI Creative Commons
Hussam N. Fakhouri, Faten Hamad, Abdelraouf Ishtaiwi

и другие.

Automation, Год журнала: 2025, Номер 6(2), С. 13 - 13

Опубликована: Март 28, 2025

This paper presents a novel Hybrid Artificial Protozoa Optimizer with Differential Evolution (HPDE), combining the biologically inspired principles of (APO) powerful optimization strategies (DE) to address complex and engineering design challenges. The HPDE algorithm is designed balance exploration exploitation features, utilizing innovative features such as autotrophic heterotrophic foraging behaviors, dormancy, reproduction processes alongside DE strategy. performance was evaluated on CEC2014 benchmark functions, it compared against two sets state-of-the-art optimizers comprising 23 different algorithms. results demonstrate HPDE’s good performance, outperforming competitors in 24 functions out 30 from first set second set. Additionally, has been successfully applied range problems, including robot gripper optimization, welded beam pressure vessel spring speed reducer cantilever three-bar truss optimization. consistently showcase solving these problems when competing

Язык: Английский

Процитировано

0

Hybrid Cuckoo Search-Gorilla Troops Optimizer for Optimal Parameter Estimation in Photovoltaic Modules DOI Creative Commons

Abdelmalek Gacem,

Ridha Kechida, Youcef Bekakra

и другие.

Journal of Engineering Research, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0