Arctic puffin optimization: A bio-inspired metaheuristic algorithm for solving engineering design optimization

Advances in Engineering Software, Journal Year: 2024, Volume and Issue: 195, P. 103694 - 103694

Published: June 15, 2024

Language: Английский

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Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules

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

Published: Feb. 11, 2024

Abstract The parameter identification problem of photovoltaic (PV) models is classified as a complex nonlinear optimization that cannot be accurately solved by traditional techniques. Therefore, metaheuristic algorithms have been recently used to solve this due their potential approximate the optimal solution for several complicated problems. Despite that, existing still suffer from sluggish convergence rates and stagnation in local optima when applied tackle problem. study presents new estimation technique, namely HKOA, based on integrating published Kepler algorithm (KOA) with ranking-based update exploitation improvement mechanisms estimate unknown parameters third-, single-, double-diode models. former mechanism aims at promoting KOA’s exploration operator diminish getting stuck optima, while latter strengthen its faster converge solution. Both KOA HKOA are validated using RTC France solar cell five PV modules, including Photowatt-PWP201, Ultra 85-P, STP6-120/36, STM6-40/36, show efficiency stability. In addition, they extensively compared techniques effectiveness. According experimental findings, strong alternative method estimating because it can yield substantially different superior findings

Language: Английский

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Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018–2023)

Energy Strategy Reviews, Journal Year: 2024, Volume and Issue: 53, P. 101409 - 101409

Published: May 1, 2024

The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling forecasting tasks. While excels in capturing intricate patterns data, it may falter achieving optimality due to nonlinear nature energy data. Conversely, offer optimization capabilities but suffer from computational burdens, especially with high-dimensional This paper provides comprehensive review spanning 2018 2023, examining integration within frameworks applications. We analyze state-of-the-art techniques, innovations, recent advancements, identifying open research challenges. Additionally, we propose novel framework that seamlessly merges into paradigms, aiming enhance performance efficiency addressing problems. contributions include: 1. Overview advancements MHs, DL, integration. 2. Coverage trends 2023. 3. Introduction Alpha metric evaluation. 4. Innovative harmonizing MHs DL

Language: Английский

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A Comprehensive Survey of Multi-Level Thresholding Segmentation Methods for Image Processing

Archives of Computational Methods in Engineering, Journal Year: 2024, Volume and Issue: 31(6), P. 3647 - 3697

Published: March 27, 2024

Language: Английский

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Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems

Heliyon, Journal Year: 2024, Volume and Issue: 10(5), P. e26665 - e26665

Published: March 1, 2024

This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel approach inspired by growth and proliferation patterns of liver tumors. MOLCA emulates evolutionary tendencies tumors, leveraging their expansion dynamics as model for solving multi-objective optimization problems in engineering design. The algorithm uniquely combines genetic operators with Random Opposition-Based Learning (ROBL) strategy, optimizing both local global search capabilities. Further enhancement is achieved through integration elitist non-dominated sorting (NDS), information feedback mechanism (IFM) Crowding Distance (CD) selection method, which collectively aim to efficiently identify Pareto optimal front. performance rigorously assessed using comprehensive set standard test benchmarks, including ZDT, DTLZ various Constraint (CONSTR, TNK, SRN, BNH, OSY KITA) real-world design like Brushless DC wheel motor, Safety isolating transformer, Helical spring, Two-bar truss Welded beam. Its efficacy benchmarked against prominent algorithms such grey wolf optimizer (NSGWO), multiobjective multi-verse (MOMVO), (NSGA-II), decomposition-based (MOEA/D) marine predator (MOMPA). Quantitative analysis conducted GD, IGD, SP, SD, HV RT metrics represent convergence distribution, while qualitative aspects are presented graphical representations fronts. source code available at: https://github.com/kanak02/MOLCA.

Language: Английский

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Orthogonal opposition-based learning honey badger algorithm with differential evolution for global optimization and engineering design problems

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 91, P. 348 - 367

Published: Feb. 19, 2024

Honey badger algorithm (HBA) is a recent swarm-based metaheuristic that excels in simplicity and high exploitation capability. However, it suffers from some limitations including weak exploration capacity an imbalance between exploitation. In this paper, improved honey called ODEHBA proposed to improve the performance of basic HBA. Firstly, orthogonal opposition-based learning technique employed assist population escaping local optimum. Secondly, differential evolution utilized ensure enrichment diversity enhance convergence speed. Finally, capability boosted by equilibrium pool strategy. To validate efficacy ODEHBA, compared with 13 well-known algorithms on CEC2022 benchmark test sets. Friedman Wilcoxon rank-sum are assess ODEHBA. Furthermore, three engineering design problems Internet Vehicles (IoV) routing problem applied The simulation results demonstrate solving complex numerical problems, design, IoV problems. This holds significant practical implications for cost reduction resource utilization.

Language: Английский

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An enhanced chameleon swarm algorithm for global optimization and multi-level thresholding medical image segmentation

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(15), P. 8775 - 8823

Published: March 5, 2024

Language: Английский

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An improved multi-strategy Golden Jackal algorithm for real world engineering problems

Knowledge-Based Systems, Journal Year: 2024, Volume and Issue: 295, P. 111725 - 111725

Published: April 16, 2024

Language: Английский

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Competitive swarm optimizer with dynamic multi-competitions and convergence accelerator for large-scale optimization problems

Applied Soft Computing, Journal Year: 2024, Volume and Issue: unknown, P. 112252 - 112252

Published: Sept. 1, 2024

Language: Английский

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Hybridizing WOA with PSO for coordinating material handling equipment in an automated container terminal considering energy consumption

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 60, P. 102410 - 102410

Published: March 6, 2024

Language: Английский

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