Solving Engineering Optimization Problems Based on Multi-Strategy Particle Swarm Optimization Hybrid Dandelion Optimization Algorithm

Biomimetics, Journal Year: 2024, Volume and Issue: 9(5), P. 298 - 298

Published: May 17, 2024

In recent years, swarm intelligence optimization methods have been increasingly applied in many fields such as mechanical design, microgrid scheduling, drone technology, neural network training, and multi-objective optimization. this paper, a multi-strategy particle hybrid dandelion algorithm (PSODO) is proposed, which based on the problems of slow speed being easily susceptible to falling into local extremum ability algorithm. This makes whole more diverse by introducing strong global search unique individual update rules (i.e., rising, landing). The ascending descending stages also help introduce changes explorations space, thus better balancing search. experimental results show that compared with other algorithms, proposed PSODO greatly improves optimal value ability, convergence speed. effectiveness feasibility are verified solving 22 benchmark functions three engineering design different complexities CEC 2005 comparing it algorithms.

Language: Английский

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A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(7)

Published: June 11, 2024

Abstract The application of optimization theory and the algorithms that are generated from it has increased along with science technology's continued advancement. Numerous issues in daily life can be categorized as combinatorial issues. Swarm intelligence have been successful machine learning, process control, engineering prediction throughout years shown to efficient handling An intelligent system called chicken swarm algorithm (CSO) mimics organic behavior flocks chickens. In benchmark problem's objective function, outperforms several popular methods like PSO. concept advancement flock algorithm, comparison other meta-heuristic algorithms, development trend reviewed order further enhance search performance quicken research algorithm. fundamental model is first described, enhanced based on parameters, chaos quantum optimization, learning strategy, population diversity then summarized using both domestic international literature. use group areas feature extraction, image processing, robotic engineering, wireless sensor networks, power. Second, evaluated terms benefits, drawbacks, algorithms. Finally, direction anticipated.

Language: Английский

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Path Planning of Unmanned Aerial Vehicles Based on an Improved Bio-Inspired Tuna Swarm Optimization Algorithm

Biomimetics, Journal Year: 2024, Volume and Issue: 9(7), P. 388 - 388

Published: June 26, 2024

The Sine-Levy tuna swarm optimization (SLTSO) algorithm is a novel method based on the sine strategy and Levy flight guidance. It presented as solution to shortcomings of (TSO) algorithm, which include its tendency reach local optima limited capacity search worldwide. This updates locations using technique greedy approach generates initial solutions an elite reverse learning process. Additionally, it offers individual location called golden sine, enhances algorithm's explore widely steer clear optima. To plan UAV paths safely effectively in complex obstacle environments, SLTSO considers constraints such geographic airspace obstacles, along with performance metrics like environment, space, distance, angle, altitude, threat levels. effectiveness verified by simulation creation path planning model. Experimental results show that displays faster convergence rates, better precision, shorter smoother paths, concomitant reduction energy usage. A drone can now map route far more thanks these improvements. Consequently, proposed demonstrates both efficacy superiority applications.

Language: Английский

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Three-Dimensional Obstacle Avoidance Harvesting Path Planning Method for Apple-Harvesting Robot Based on Improved Ant Colony Algorithm

Agriculture, Journal Year: 2024, Volume and Issue: 14(8), P. 1336 - 1336

Published: Aug. 10, 2024

The cultivation model for spindle-shaped apple trees is widely used in modern standard orchards worldwide and represents the direction of industry development. However, without an effective obstacle avoidance path, robotic arm prone to collision with obstacles such as fruit tree branches during picking process, which may damage fruits even affect healthy growth trees. To address above issues, a three-dimensional path -planning algorithm full-field harvesting trees, are planted orchards, proposed this study. Firstly, based on three typical structures (free spindle, high slender spindle), spatial was established. Secondly, grid environment representation method, map Then, initial pheromones were improved by non-uniform distribution basis original ant colony algorithm. Furthermore, updating rules improved, biomimetic optimization mechanism integrated beetle antenna improve speed stability searching. Finally, planned smoothed using cubic B-spline curve make smoother avoid unnecessary pauses or turns process arm. Based ACO (ant algorithm), 3D planning simulation experiments conducted types results showed that success rates higher than 96%, 86%, 92% free-spindle-shaped, high-spindle-shaped, slender-spindle-shaped respectively. Compared traditional algorithms, average time decreased 49.38%, 46.33%, 51.03%, can effectively achieve picking, thereby providing technical support development intelligent robots.

Language: Английский

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Heuristic Optimization Algorithm of Black-Winged Kite Fused with Osprey and Its Engineering Application

Biomimetics, Journal Year: 2024, Volume and Issue: 9(10), P. 595 - 595

Published: Oct. 1, 2024

Swarm intelligence optimization methods have steadily gained popularity as a solution to multi-objective issues in recent years. Their study has garnered lot of attention since problems hard high-dimensional goal space. The black-winged kite algorithm still suffers from the imbalance between global search and local development capabilities, it is prone even though combines Cauchy mutation enhance algorithm's ability. heuristic fused with osprey (OCBKA), which initializes population by logistic chaotic mapping fuses improve performance algorithm, proposed means enhancing ability (BKA). By using numerical comparisons CEC2005 CEC2021 benchmark functions, along other swarm solutions three engineering problems, upgraded strategy's efficacy confirmed. Based on experiment findings, revised OCBKA very competitive because can handle complicated high convergence accuracy quick time when compared comparable algorithms.

Language: Английский

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FOX Optimization Algorithm Based on Adaptive Spiral Flight and Multi-Strategy Fusion

Biomimetics, Journal Year: 2024, Volume and Issue: 9(9), P. 524 - 524

Published: Aug. 30, 2024

Adaptive spiral flight and multi-strategy fusion are the foundations of a new FOX optimization algorithm that aims to address drawbacks original method, including weak starting individual ergodicity, low diversity, an easy way slip into local optimum. In order enhance population, inertial weight is added along with Levy variable strategy once population initialized using tent chaotic map. To begin process implementing fox position created Tent map in provide more ergodic varied beginning locations. improve quality solution, second place. The random walk mode then updated updating approach. Subsequently, algorithm’s global searches balanced, flying method greedy approach incorporated update location. enhanced technique thoroughly contrasted various swarm intelligence algorithms engineering application issues CEC2017 benchmark test functions. According simulation findings, there have been notable advancements convergence speed, accuracy, stability, as well jumping out optimum, upgraded algorithm.

Language: Английский

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Snake Optimization Algorithm Augmented by Adaptive t-Distribution Mixed Mutation and Its Application in Energy Storage System Capacity Optimization

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 244 - 244

Published: April 16, 2025

To address the drawbacks of traditional snake optimization method, such as a random population initialization, slow convergence speed, and low accuracy, an adaptive t-distribution mixed mutation strategy is proposed. Initially, Tent-based chaotic mapping quasi-reverse learning approach are utilized to enhance quality initial solution initialization process original method. During evolution stage, novel foraging introduced substitute stage This perturbs mutates at optimal position generate new solutions, thereby improving algorithm’s ability escape local optima. The mating mode in replaced with opposite-sex attraction mechanism, providing algorithm more opportunities for global exploration exploitation. improved method accelerates improves accuracy while balancing exploitation capabilities. experimental results demonstrate that outperforms other methods, including standard technique, terms robustness accuracy. Additionally, each improvement technique complements amplifies effects others.

Language: Английский

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A machine learning approach to predicting pervious concrete properties: a review

Innovative Infrastructure Solutions, Journal Year: 2025, Volume and Issue: 10(2)

Published: Jan. 23, 2025

Language: Английский

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Optimization of Natural Ventilation via Computational Fluid Dynamics Simulation and Hybrid Beetle Antennae Search and Particle Swarm Optimization Algorithm for Yungang Grottoes, China

Buildings, Journal Year: 2025, Volume and Issue: 15(6), P. 937 - 937

Published: March 16, 2025

The Yungang Grottoes are undergoing degradation by weather and environmental erosion. Here, we propose a natural ventilation strategy to optimize the environments in Cave 9 10 of Grottoes. novelty this work is use an effective computational fluid dynamics (CFD) simulation hybrid beetle antennae search particle swarm optimization algorithms (BAS–PSO) determine which scenario yields maximum total heat transfer rate (Qmax). A CFD hygrothermal model first developed shows high precision predicting temperature humidity conditions based on real-time measured data. efficiency enhanced different configurations doors windows with four rates. Combined eXtreme Gradient Boosting (XGBoost) fitting, BAS–PSO algorithm largest Qmax (5746.74 W), further confirmed simulations outcome comparable (5730.67 W). It indicates that exhibits good performance identification optimal configurations. effectiveness proposed verified on-site Our findings provide beneficial energy-efficient preservation

Language: Английский

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Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique

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

Published: April 23, 2025

Language: Английский

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