An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning

Biomimetics, Год журнала: 2025, Номер 10(1), С. 23 - 23

Опубликована: Янв. 3, 2025

To address the challenges of slow convergence speed, poor precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). First, mathematical model is used to construct terrain environment, multi-constraint cost established, framing as multidimensional function optimization problem. Second, recognizing sensitivity population diversity Logistic Chaotic Mapping traditional (HEOA), opposition-based learning strategy employed uniformly initialize distribution, thereby enhancing algorithm’s global capability. Additionally, guidance factor introduced into leader role during development stage, providing clear directionality search process, which increases probability selecting optimal paths accelerates speed. Furthermore, loser update strategy, adaptive t-distribution perturbation utilized its small mutation amplitude, enhances capability robustness algorithm. Evaluations using 12 standard test functions demonstrate that these improvement strategies effectively enhance precision algorithm stability, with IHEOA, integrates multiple strategies, performing particularly well. Experimental comparative research three different environments five algorithms shows IHEOA not only exhibits excellent performance terms speed but also generates superior while demonstrating exceptional complex environments. These results validate significant advantages proposed improved addressing UAV challenges.

Язык: Английский

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An Improved Triangular Mutated Slime Mould Algorithm for Developing an Optimized Frequency Control of a Bi-zonal Islanded Microgrid Power System

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104306 - 104306

Опубликована: Фев. 1, 2025

Язык: Английский

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MEARO: A multi-strategy enhanced artificial rabbits optimization for global optimization problems

Cluster Computing, Год журнала: 2025, Номер 28(4)

Опубликована: Фев. 25, 2025

Язык: 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, Год журнала: 2025, Номер 10(4), С. 244 - 244

Опубликована: Апрель 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.

Язык: Английский

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Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

PLoS ONE, Год журнала: 2023, Номер 18(1), С. e0280512 - e0280512

Опубликована: Янв. 25, 2023

In this article, an improved slime mould algorithm (SMA-CSA) is proposed for solving global optimization and the capacitated vehicle routing problem (CVRP). This improvement based on mixed-strategy of Cauchy mutation simulated annealing to alleviate lack capability SMA. By introducing strategy, optimal solution perturbed increase probability escaping from local extreme value; in addition, strategy introduced, Metropolis sampling criterion used as acceptance expand search space enhance exploration phase achieve solutions. The performance SMA-CSA evaluated using CEC 2013 benchmark functions problem. all experiments, compared with ten other state-of-the-art metaheuristics. results are also analyzed by Friedman Wilcoxon rank-sum test. experimental statistical tests demonstrate that very competitive often superior algorithms experiments. its efficiency discrete ability.

Язык: Английский

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Bald eagle search algorithm for solving a three-dimensional path planning problem

Mathematical Biosciences & Engineering, Год журнала: 2024, Номер 21(2), С. 2856 - 2878

Опубликована: Янв. 1, 2024

<abstract> <p>Three-dimensional path planning refers to determining an optimal in a three-dimensional space with obstacles, so that the is as close target location possible, while meeting some other constraints, including distance, altitude, threat area, flight time, energy consumption, and on. Although bald eagle search algorithm has characteristics of simplicity, few control parameters, strong global capabilities, it not yet been applied complex problems. In order broaden application scenarios scope solve problem space, we present study where five geographical environments are simulated represent real-life unmanned aerial vehicles flying scenarios. These maps effectively test algorithm's ability handle various terrains, extreme environments. The experimental results have verified excellent performance BES algorithm, which can quickly, stably, problems, making highly competitive this field.</p> </abstract>

Язык: Английский

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Equilibrium Optimizer and Slime Mould Algorithm with Variable Neighborhood Search for Job Shop Scheduling Problem

Mathematics, Год журнала: 2022, Номер 10(21), С. 4063 - 4063

Опубликована: Ноя. 1, 2022

Job Shop Scheduling Problem (JSSP) is a well-known NP-hard combinatorial optimization problem. In recent years, many scholars have proposed various metaheuristic algorithms to solve JSSP, playing an important role in solving small-scale JSSP. However, when the size of problem increases, usually take too much time converge. this paper, we propose hybrid algorithm, namely EOSMA, which mixes update strategy Equilibrium Optimizer (EO) into Slime Mould Algorithm (SMA), adding Centroid Opposition-based Computation (COBC) some iterations. The hybridization EO with SMA makes better balance between exploration and exploitation. addition COBC strengthens exploitation, increases diversity population, improves convergence speed accuracy, avoids falling local optimum. order discrete problems efficiently, Sort-Order-Index (SOI)-based coding method proposed. JSSP more neighbor search based on two-point exchange added iterative process EOSMA improve exploitation capability Then, it utilized 82 benchmark instances; its performance evaluated compared that EO, Marine Predators (MPA), Aquila (AO), Bald Eagle Search (BES), SMA. experimental results statistical analysis show outperforms other competing algorithms.

Язык: Английский

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Letter: Application of optimization algorithms to engineering design problems and discrepancies in mathematical formulas

Applied Soft Computing, Год журнала: 2023, Номер 140, С. 110252 - 110252

Опубликована: Март 25, 2023

Язык: Английский

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Non-Destructive Detection of Different Pesticide Residues on the Surface of Hami Melon Classification Based on tHBA-ELM Algorithm and SWIR Hyperspectral Imaging

Foods, Год журнала: 2023, Номер 12(9), С. 1773 - 1773

Опубликована: Апрель 25, 2023

In the field of safety detection fruits and vegetables, how to conduct non-destructive pesticide residues is still a pressing problem be solved. response high cost destructive nature existing chemical methods, this study explored potential identifying different on Hami melon by short-wave infrared (SWIR) (spectral range 1000-2500 nm) hyperspectral imaging (HSI) technology combined with machine learning. Firstly, classification effects classical models, namely extreme learning (ELM), support vector (SVM), partial least squares discriminant analysis (PLS-DA) were compared, ELM was selected as benchmark model for subsequent optimization. Then, preprocessing treatments compared analyzed determine most suitable spectral treatment. The optimized Honey Badger Algorithm (HBA) adaptive t-distribution mutation strategy (tHBA-ELM) proposed improve accuracy melon. primitive HBA algorithm using t-distribution, which improved structure population increased convergence speed. Compared results tHBA-ELM HBA-ELM genetic (GA-ELM), can accurately identify whether there types pesticides. accuracy, precision, sensitivity, F1-score test set 93.50%, 93.73%, 0.9355, respectively. Metaheuristic optimization algorithms performance models. Among all satisfactory. indicated that SWIR-HSI coupled used melon, provided theoretical basis technical reference in other vegetables.

Язык: Английский

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An improved slime mould algorithm using multiple strategies

International Journal of Parallel Emergent and Distributed Systems, Год журнала: 2024, Номер 39(4), С. 461 - 485

Опубликована: Май 13, 2024

Aiming at the defects of standard slime mould algorithm (SMA), such as local optima stagnation, slow convergence and improper balance between exploitation exploration, we propose an improved SMA that contains adaptive t-distributed variation strategy, location update formula chaotic opposition-based learning is, MISMA. Utilizing comparative experiments ablation studies on classical benchmark CEC2020 suite, proved MISMA outperforms other state-of-the-art rival algorithms speed, solution accuracy, robustness, each component achieves improvement stage exhibits synergistic effects.

Язык: Английский

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