An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4992 - 4992

Published: April 30, 2025

Flower collection constitutes a critical segment of the flower logistics chain, and its efficiency significantly influences industry. However, energy consumption carbon emissions that occur in process present great challenge for realizing efficient collection. To this end, study proposes green vehicle routing planning model incorporates multiple factors, such as fixed costs, refrigeration transportation so on, to minimize total costs under hard time window constraints. Moreover, Genetic Neighborhood Comprehensive Spider Wasp Algorithm (GN_CSWA) is proposed find solution problem. The random generation nearest neighbor algorithms are employed construct initial solution, followed by roulette selection, elite best individual retention strategy refine population next iteration. A crossover operator applied facilitate global exploration, while six neighborhood search operators further enhance quality solution. prevent algorithm from converging local optimum, two mutation introduced generate new solutions. effectiveness optimizer validated through extensive experimental results.

Language: Английский

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Spider Wasp Optimizer-Optimized Cascaded Fractional-Order Controller for Load Frequency Control in a Photovoltaic-Integrated Two-Area System

Mathematics, Journal Year: 2024, Volume and Issue: 12(19), P. 3076 - 3076

Published: Sept. 30, 2024

The integration of photovoltaic (PV) systems into traditional power grids introduces significant challenges in maintaining system stability, particularly multi-area systems. This study proposes a novel approach to load frequency control (LFC) two-area system, where one area is powered by PV grid and the other thermal generator. To enhance performance, cascaded strategy combining fractional-order proportional–integral (FOPI) controller proportional–derivative with filter (PDN) controller, FOPI(1+PDN), introduced. parameters are optimized using spider wasp optimizer (SWO). Extensive simulations conducted validate effectiveness SWO-tuned FOPI(1+PDN) controller. proposed method demonstrates superior performance reducing deviations tie-line fluctuations under various disturbances. results compared against advanced optimization algorithms, each applied Additionally, this benchmarks recently reported strategies that were different algorithms. terms faster response, reduced overshoot undershoot, better error minimization.

Language: Английский

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An optimization-inspired intrusion detection model for software-defined networking

Electronic Research Archive, Journal Year: 2025, Volume and Issue: 33(1), P. 231 - 254

Published: Jan. 1, 2025

<p>As an emerging network architecture, software-defined networking (SDN) has the core concept of separating control plane from hardware and unifying its management by a central controller. Since centralized SDN is such that attack on controller can lead to paralysis entire network, intrusion detection become particularly significant for SDN. Currently, more systems based machine learning deep are being applied SDN, but most have drawbacks as complex models low accuracy. This paper proposes enhanced spider wasp optimizer (ESWO) algorithm feature dimensionality reduction datasets constructs new model (IDM), namely ESWO-IDM, The ESWO integrates multiple strategies, including tent chaotic map strategy elite opposition improve diversity population, Lévy flight prevent falling into local optimum in early stage, dynamic adjustment parameters balance exploration exploitation algorithm. was empirically evaluated using eight benchmark test functions four UCI comprehensively demonstrate advantages. Binary multiclassification experiments were conducted InSDN dataset analyze ESWO-IDM performance compare it with other IDMs. experimental results show achieves best all metrics both binary classification prominent effect normal, denial service (DoS), distributed DoS, Brute Force Attack types, which effectively improves viewpoint optimization.</p>

Language: Английский

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An optimization-inspired intrusion detection model for software-defined networking

Electronic Research Archive, Journal Year: 2025, Volume and Issue: 33(1), P. 231 - 251

Published: Jan. 1, 2025

<p>As an emerging network architecture, software-defined networking (SDN) has the core concept of separating control plane from hardware and unifying its management by a central controller. Since centralized SDN is such that attack on controller can lead to paralysis entire network, intrusion detection become particularly significant for SDN. Currently, more systems based machine learning deep are being applied SDN, but most have drawbacks as complex models low accuracy. This paper proposes enhanced spider wasp optimizer (ESWO) algorithm feature dimensionality reduction datasets constructs new model (IDM), namely ESWO-IDM, The ESWO integrates multiple strategies, including tent chaotic map strategy elite opposition improve diversity population, Lévy flight prevent falling into local optimum in early stage, dynamic adjustment parameters balance exploration exploitation algorithm. was empirically evaluated using eight benchmark test functions four UCI comprehensively demonstrate advantages. Binary multiclassification experiments were conducted InSDN dataset analyze ESWO-IDM performance compare it with other IDMs. experimental results show achieves best all metrics both binary classification prominent effect normal, denial service (DoS), distributed DoS, Brute Force Attack types, which effectively improves viewpoint optimization.</p>

Language: Английский

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Solving single- and multi-objective optimal power flow problems using the spider wasp optimization algorithm

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 21, 2025

Language: Английский

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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer

Drones, Journal Year: 2025, Volume and Issue: 9(5), P. 326 - 326

Published: April 23, 2025

This paper proposes a Kalman filter-based cascaded PI-(1+PI) controller, optimized using an Improved Spider Wasp Optimizer (ISWO), to address the challenges of USV heading control in dynamic marine environments. Traditional PID controllers struggle with nonlinearities and noise systems while existing metaheuristic algorithms face limitations balancing exploration exploitation. To overcome these issues, ISWO integrates adaptive grouping, perturbation dimension-symmetric distance optimization, nonlinear time-varying weights, enhancing convergence speed optimization accuracy. A transfer function model system is established voyage data, optimizing its parameters, achieving 5.67% reduction mean squared error (MSE) compared original outperforming classical like Arithmetic Optimization Algorithm (AOA), Crayfish (COA), Marine Predators (MPA). The proposed KF-PI(1+PI) controller incorporates filter suppress structure improve gain response speed, reducing integrated time absolute (ITAE) by 84% relative traditional controllers. hardware-in-the-loop simulation experiments further validate controller’s robustness. study demonstrates that ISWO-optimized significantly enhance navigation precision adaptability, offering viable solution for autonomous operations.

Language: Английский

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Augmented electric eel foraging optimization algorithm for feature selection with high-dimensional biological and medical diagnosis

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 18, 2024

Language: Английский

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Improved Salp Swarm Optimization Algorithm based on a Robust Search Strategy and a Novel Local Search Algorithm for Feature Selection Problems

Chemometrics and Intelligent Laboratory Systems, Journal Year: 2025, Volume and Issue: 258, P. 105343 - 105343

Published: Feb. 7, 2025

Language: Английский

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Designing Effective Drug Therapies Using a Multiobjective Spider-Wasp Optimizer

Biomimetics, Journal Year: 2025, Volume and Issue: 10(4), P. 219 - 219

Published: April 2, 2025

Designing effective drug therapies requires balancing competing objectives, such as therapeutic efficacy, safety, and cost efficiency—a task that poses significant challenges for conventional optimization methods. To address this, we propose the multi-objective spider–wasp optimizer (MOSWO), a novel approach uniquely emulating cooperative predation dynamics between spiders wasps observed in nature. MOSWO integrates adaptive mechanisms exploration exploitation to resolve complex trade-offs multiobjective design. Unlike existing approaches, algorithm employs dynamic population-partitioning strategy inspired by predator–prey interactions, enabling efficient Pareto frontier discovery. We validate MOSWO’s performance through extensive experiments on synthetic benchmarks real-world case studies spanning antiviral antibiotic therapies. Results demonstrate surpasses state-of-the-art methods (NSGA-II, MOEA/D, MOGWO, MOPSO), achieving 11% higher hypervolume scores, 8% lower inverted generational distance 9% spread 30% faster convergence, superior robustness against noisy biological datasets. The framework’s adaptability diverse scenarios underscores its potential transformative tool computational pharmacology.

Language: Английский

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Bi-objective feature selection in high-dimensional datasets using improved binary chimp optimization algorithm

International Journal of Machine Learning and Cybernetics, Journal Year: 2024, Volume and Issue: 15(12), P. 6107 - 6148

Published: Aug. 10, 2024

Language: Английский

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