Improved multi-strategy beluga whale optimization algorithm: a case study for multiple engineering optimization problems

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(3)

Published: Jan. 21, 2025

Language: Английский

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IRIME: Mitigating exploitation-exploration imbalance in RIME optimization for feature selection

iScience, Journal Year: 2024, Volume and Issue: 27(8), P. 110561 - 110561

Published: July 22, 2024

Rime optimization algorithm (RIME) encounters issues such as an imbalance between exploitation and exploration, susceptibility to local optima, low convergence accuracy when handling problems. This paper introduces a variant of RIME called IRIME address these drawbacks. integrates the soft besiege (SB) composite mutation strategy (CMS) restart (RS). To comprehensively validate IRIME's performance, IEEE CEC 2017 benchmark tests were conducted, comparing it against many advanced algorithms. The results indicate that performance is best. In addition, applying in four engineering problems reflects solving practical Finally, proposes binary version, bIRIME, can be applied feature selection bIRIMR performs well on 12 low-dimensional datasets 24 high-dimensional datasets. It outperforms other algorithms terms number subsets classification accuracy. conclusion, bIRIME has great potential selection.

Language: Английский

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Marine diesel engine piston ring fault diagnosis based on LSTM and improved beluga whale optimization

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 109, P. 213 - 228

Published: Sept. 5, 2024

Language: Английский

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A dual opposition learning-based multi-objective Aquila Optimizer for trading-off time-cost-quality-CO₂ emissions of generalized construction projects

Engineering Computations, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 18, 2024

Purpose Most of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical activity and characteristics into account. This study aims to present novel approach called “hybrid opposition learning-based Aquila Optimizer” (HOLAO) for optimizing TCQET decisions in generalized construction projects. Design/methodology/approach In this paper, HOLAO algorithm is designed, incorporating quasi-opposition-based learning (QOBL) quasi-reflection-based (QRBL) strategies initial population generation jumping phases, respectively. The crowded distance rank (CDR) mechanism utilized optimal Pareto-front solutions assist decision-makers (DMs) achieving single compromise solution. Findings efficacy proposed methodology evaluated by examining problems, involving 69 290 activities, Results indicate that provides competitive problems It observed surpasses multiple objective social group optimization (MOSGO), plain Optimization (AO), QRBL QOBL algorithms terms both number function evaluations (NFE) hypervolume (HV) indicator. Originality/value paper introduces concept hybrid opposition-based (HOL), which incorporates two strategies: as an explorative exploitative opposition. Achieving effective balance between exploration exploitation crucial success any algorithm. To end, are developed ensure proper equilibrium phases basic AO third contribution provide resource utilizations (construction plans) evaluate these resources performance.

Language: Английский

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IBWC: a user-centric approach to multi-objective cloud task scheduling using improved beluga whale optimization

Knowledge and Information Systems, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 12, 2025

Language: Английский

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A black-winged kite optimization algorithm enhanced by osprey optimization and vertical and horizontal crossover improvement

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 25, 2025

This paper addresses issues of inadequate accuracy and inconsistency between global search efficacy local development capability in the black-winged kite algorithm for practical problem-solving by proposing a optimization that integrates Osprey Crossbar enhancement (DKCBKA). Firstly, adaptive index factor fusion Optimization Algorithm approach are incorporated to enhance algorithm's convergence rate, probability distribution is updated throughout attack stage. Second, stochastic difference variant method implemented prevent from entering optima. Lastly, longitudinal transversal crossover technique dynamically alter population's individual optimal solutions. Fifteen benchmark functions chosen test effectiveness enhanced compare efficiency each technique. Simulation experiments performed on CEC2017 CEC2019 sets, revealing DKCBKA surpasses five standard swarm intelligence methods six improved algorithms regarding solution speed. The superiority meeting real challenges further demonstrated three engineering problems DKCBKA, with capabilities 18.222%, 99.885% 0.561% higher than BKA, respectively.

Language: Английский

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A survey of Beluga whale optimization and its variants: Statistical analysis, advances, and structural reviewing

Computer Science Review, Journal Year: 2025, Volume and Issue: 57, P. 100740 - 100740

Published: March 3, 2025

Language: Английский

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A Novel Hybrid Algorithm Based on Beluga Whale Optimization and Harris Hawks Optimization for Optimizing Multi-Reservoir Operation

Water Resources Management, Journal Year: 2024, Volume and Issue: 38(12), P. 4883 - 4909

Published: June 19, 2024

Language: Английский

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A Bionic-Based Multi-Objective Optimization for a Compact HVAC System with Integrated Air Conditioning, Purification, and Humidification

Biomimetics, Journal Year: 2025, Volume and Issue: 10(3), P. 159 - 159

Published: March 3, 2025

This study is dedicated to the development of a multifunctional device that integrates air conditioning, humidification, and purification functions, aimed at meeting demands for energy efficiency, space-saving, comfortable indoor environments in modern residential commercial settings. The research focuses on achieving balance between performance, consumption, noise levels by combining bionic design principles with advanced optimization algorithms propose innovative methods. Specific methods include establishment mathematical models purification, humidification functions. conditioning module employs nonlinear programming model optimized through Parrot Optimizer (PO) Algorithm achieve uniform temperature distribution minimal consumption. function based using Deep ACO ensure high efficiency low levels. utilizes mist diffusion Slime Mold (SMA) enhance performance. Ultimately, multi-objective constructed Beluga Whale Optimization (BWO), successfully integrating three main functions designing compact segmented cylindrical achieves multifunctionality. results indicate exhibits superior Clean Air Delivery Rate (CADR) 400 m3/h, rate 1.2 kg/h, uniformity index 0.08, total power consumption controlled within 1600 W. demonstrates significant potential technology environment control devices, enhancing not only overall performance but also comfort sustainability environment. Future work will focus system scalability, experimental validation, further characteristics expand device’s applicability its environmental adaptability.

Language: Английский

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A multi-strategy improved rime optimization algorithm for three-dimensional USV path planning and global optimization

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

Published: June 1, 2024

The RIME optimization algorithm (RIME) represents an advanced technique. However, it suffers from issues such as slow convergence speed and susceptibility to falling into local optima. In response these shortcomings, we propose a multi-strategy enhanced version known the improved (MIRIME). Firstly, Tent chaotic map is utilized initialize population, laying groundwork for global optimization. Secondly, introduce adaptive update strategy based on leadership dynamic centroid, facilitating swarm's exploitation in more favorable direction. To address problem of population scarcity later iterations, lens imaging opposition-based learning control introduced enhance diversity ensure accuracy. proposed centroid boundary not only limits search boundaries individuals but also effectively enhances algorithm's focus efficiency. Finally, demonstrate performance MIRIME, employ CEC 2017 2022 test suites compare with 11 popular algorithms across different dimensions, verifying its effectiveness. Additionally, assess method's practical feasibility, apply MIRIME solve three-dimensional path planning unmanned surface vehicles. Experimental results indicate that outperforms other competing terms solution quality stability, highlighting superior application potential.

Language: Английский

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