CGJO: a novel complex-valued encoding golden jackal optimization DOI Creative Commons
Jinzhong Zhang, Gang Zhang,

Min Kong

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 23, 2024

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing encompassing, capturing prey to refresh a jackal's position. However, the GJO has several limitations, such as slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, weak exploration exploitation. To enhance global detection ability this paper proposes novel complex-valued encoding golden (CGJO) achieve function engineering design. The strategy deploys dual-diploid organization encode real imaginary portions of converts dual-dimensional region single-dimensional manifestation region, increases population diversity, restricts search stagnation, expands area, promotes information exchange, fosters collaboration efficiency improves accuracy. CGJO not only exhibits strong adaptability robustness supplementary advantages but also balances local exploitation promote precision determine best solution. CEC 2022 test suite six real-world designs are utilized evaluate effectiveness feasibility CGJO. compared with three categories existing algorithms: (1) WO, HO, NRBO BKA recently published algorithms; (2) SCSO, GJO, RGJO SGJO highly cited (3) L-SHADE, LSHADE-EpsSin CMA-ES performing algorithms. experimental results reveal that superior those other superiority reliability quicker greater computation precision, stability robustness.

Language: Английский

Blood-sucking leech optimizer DOI
Jianfu Bai, H. Nguyen‐Xuan, Elena Atroshchenko

et al.

Advances in Engineering Software, Journal Year: 2024, Volume and Issue: 195, P. 103696 - 103696

Published: June 15, 2024

Language: Английский

Citations

21
A multi-objective optimization of porous sandwich functionally graded plates with graphene nanoplatelet reinforcement using Blood-Sucking leech Optimizer DOI
Jianfu Bai, Nam V. Nguyen, H. Nguyen‐Xuan

et al.

Composite Structures, Journal Year: 2025, Volume and Issue: unknown, P. 118921 - 118921

Published: Feb. 1, 2025

Language: Английский

Citations

0
A comprehensive survey of golden jacal optimization and its applications DOI
Mehdi Hosseinzadeh, Jawad Tanveer, Amir Masoud Rahmani

et al.

Computer Science Review, Journal Year: 2025, Volume and Issue: 56, P. 100733 - 100733

Published: Feb. 11, 2025

Language: Английский

Citations

0
Multi-Strategy Golden Jackal Optimization for engineering design DOI
Wenbiao Yang,

Thin Lai,

Yangwang Fang

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(4)

Published: March 13, 2025

Language: Английский

Citations

0
A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods DOI Creative Commons
Mehdi Ghasri, Hamid Reza Karimi, Abdolhamid Salarnia

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105020 - 105020

Published: April 1, 2025

Language: Английский

Citations

0
An efficient multi-objective algorithm based on Rao and differential evolution for solving bi-objective truss optimization DOI

Manh-Cuong Nguyen,

Hoang-Anh Pham, Viet-Hung Truong

et al.

Engineering Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 31

Published: Feb. 24, 2025

Language: Английский

Citations

0
A novel reward-based golden jackal optimization algorithm uses mix-weighted dynamic and random opposition learning to solve optimization problems DOI

Sarada Mohapatra,

Priteesha Sarangi,

Prabhujit Mohapatra

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

Citations

0
Data-Driven Golden Jackal Optimization–Long Short-Term Memory Short-Term Energy-Consumption Prediction and Optimization System DOI Creative Commons
Yongjie Yang,

Yulong Li,

Yan Cai

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(15), P. 3738 - 3738

Published: July 29, 2024

In order to address the issues of significant energy and resource waste, low-energy management efficiency, high building-maintenance costs in hot-summer cold-winter regions China, a research project was conducted on an office building located Nantong. this study, data-driven golden jackal optimization (GJO)-based Long Short-Term Memory (LSTM) short-term energy-consumption prediction system is proposed. The creates equivalent model employs genetic algorithm tool Wallacei automatically optimize control building’s air conditioning system, thereby achieving objective reducing consumption. To validate authenticity scheme, unoptimized consumption predicted using consumption-prediction model. actual comparison data confirmed that reduction resulted from implementing conditioning-optimization scheme rather than external factors. optimized can achieve hourly saving rate 6% 9%, with average daily energy-saving reaching 8%. entire therefore, enables decision-makers swiftly assess efficacy consumption-optimization programs, furnishing scientific foundation for real-world buildings.

Language: Английский

Citations

1
CGJO: a novel complex-valued encoding golden jackal optimization DOI Creative Commons
Jinzhong Zhang, Gang Zhang,

Min Kong

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 23, 2024

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing encompassing, capturing prey to refresh a jackal's position. However, the GJO has several limitations, such as slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, weak exploration exploitation. To enhance global detection ability this paper proposes novel complex-valued encoding golden (CGJO) achieve function engineering design. The strategy deploys dual-diploid organization encode real imaginary portions of converts dual-dimensional region single-dimensional manifestation region, increases population diversity, restricts search stagnation, expands area, promotes information exchange, fosters collaboration efficiency improves accuracy. CGJO not only exhibits strong adaptability robustness supplementary advantages but also balances local exploitation promote precision determine best solution. CEC 2022 test suite six real-world designs are utilized evaluate effectiveness feasibility CGJO. compared with three categories existing algorithms: (1) WO, HO, NRBO BKA recently published algorithms; (2) SCSO, GJO, RGJO SGJO highly cited (3) L-SHADE, LSHADE-EpsSin CMA-ES performing algorithms. experimental results reveal that superior those other superiority reliability quicker greater computation precision, stability robustness.

Language: Английский

Citations

1