A Novel Hybrid Improved RIME Algorithm for Global Optimization Problems DOI Creative Commons

Wuke Li,

Xiong Yang,

Yuchen Yin

и другие.

Biomimetics, Год журнала: 2024, Номер 10(1), С. 14 - 14

Опубликована: Дек. 31, 2024

The RIME algorithm is a novel physical-based meta-heuristic with strong ability to solve global optimization problems and address challenges in engineering applications. It implements exploration exploitation behaviors by constructing rime-ice growth process. However, comes couple of disadvantages: limited exploratory capability, slow convergence, inherent asymmetry between exploitation. An improved version more efficiency adaptability these issues now the form Hybrid Estimation Rime-ice Optimization, short, HERIME. A probabilistic model-based sampling approach estimated distribution utilized enhance quality population boost its capability. roulette-based fitness distance balanced selection strategy used strengthen hard-rime phase effectively balance phases We validate HERIME using 41 functions from IEEE CEC2017 CEC2022 test suites compare accuracy, stability four classical recent metaheuristic algorithms as well five advanced reveal fact that proposed outperforms all them. Statistical research Friedman Wilcoxon rank sum also confirms excellent performance. Moreover, ablation experiments effectiveness each individually. Thus, experimental results show has better search accuracy effective dealing problems.

Язык: Английский

An efficient multi-objective parrot optimizer for global and engineering optimization problems DOI Creative Commons

Mohammed R. Saad,

Marwa M. Emam,

Essam H. Houssein

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 11, 2025

Abstract The Parrot Optimizer (PO) has recently emerged as a powerful algorithm for single-objective optimization, known its strong global search capabilities. This study extends PO into the Multi-Objective (MOPO), tailored multi-objective optimization (MOO) problems. MOPO integrates an outward archive to preserve Pareto optimal solutions, inspired by behavior of Pyrrhura Molinae parrots. Its performance is validated on Congress Evolutionary Computation 2020 (CEC’2020) benchmark suite. Additionally, extensive testing four constrained engineering design challenges and eight popular confined unconstrained test cases proves MOPO’s superiority. Moreover, real-world helical coil springs automotive applications conducted depict reliability proposed in solving practical Comparative analysis was performed with seven published, state-of-the-art algorithms chosen their proven effectiveness representation current research landscape-Improved Manta-Ray Foraging Optimization (IMOMRFO), Gorilla Troops (MOGTO), Grey Wolf (MOGWO), Whale Algorithm (MOWOA), Slime Mold (MOSMA), Particle Swarm (MOPSO), Non-Dominated Sorting Genetic II (NSGA-II). results indicate that consistently outperforms these across several key metrics, including Set Proximity (PSP), Inverted Generational Distance Decision Space (IGDX), Hypervolume (HV), (GD), spacing, maximum spread, confirming potential robust method addressing complex MOO

Язык: Английский

Процитировано

0
Optimized design and integration of an off-grid solar PV-biomass-battery hybrid energy system using an enhanced educational competition algorithm for cost-effective rural electrification DOI

Marwa M. Emam,

Hoda Abd El-Sattar, Essam H. Houssein

и другие.

Journal of Energy Storage, Год журнала: 2025, Номер 120, С. 116381 - 116381

Опубликована: Апрель 9, 2025

Язык: Английский

Процитировано

0
A Novel Hybrid Improved RIME Algorithm for Global Optimization Problems DOI Creative Commons

Wuke Li,

Xiong Yang,

Yuchen Yin

и другие.

Biomimetics, Год журнала: 2024, Номер 10(1), С. 14 - 14

Опубликована: Дек. 31, 2024

The RIME algorithm is a novel physical-based meta-heuristic with strong ability to solve global optimization problems and address challenges in engineering applications. It implements exploration exploitation behaviors by constructing rime-ice growth process. However, comes couple of disadvantages: limited exploratory capability, slow convergence, inherent asymmetry between exploitation. An improved version more efficiency adaptability these issues now the form Hybrid Estimation Rime-ice Optimization, short, HERIME. A probabilistic model-based sampling approach estimated distribution utilized enhance quality population boost its capability. roulette-based fitness distance balanced selection strategy used strengthen hard-rime phase effectively balance phases We validate HERIME using 41 functions from IEEE CEC2017 CEC2022 test suites compare accuracy, stability four classical recent metaheuristic algorithms as well five advanced reveal fact that proposed outperforms all them. Statistical research Friedman Wilcoxon rank sum also confirms excellent performance. Moreover, ablation experiments effectiveness each individually. Thus, experimental results show has better search accuracy effective dealing problems.

Язык: Английский

Процитировано

0