Multi-Objective Water Strider Algorithm for Complex Structural Optimization: A Comprehensive Performance Analysis DOI Creative Commons
Kanak Kalita,

N. Ganesh,

Rama Chandran Narayanan

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 55157 - 55183

Published: Jan. 1, 2024

For various daunting physical world structural optimization design problems, a novel multi-objective water strider algorithm (MOWSA) is proposed, and its non-dominated sorting (NDS) framework explored. This effort inspired by the recent proposals for Water Strider Algorithm, population-based mathematical paradigm focused on lifespan of insects. The crowding distance characteristic integrated into MOSWA to improve exploration exploitation trade-off behavior during advancement quest. Furthermore, suggested posteriori approach exercises NDS technique maintain population diversity, key issue in meta-heuristics, especially optimization. Structural mass reduction nodal deflection maximization are two diverse objectives posed problems. At same time, stress components discrete cross-sectional areas imposed safety side constraints, respectively. Eight planar spatial truss problems demonstrate utility proposed solving complex where performance analysis based ten globally accepted metrics. Moreover, outcomes were compared with four state-of-the-art techniques measure viability algorithm. outperforms other considered algorithms concerning computational run achieve optimal solutions their qualitative over Pareto fronts.

Language: Английский

A New Arithmetic Optimization Algorithm for Solving Real-World Multiobjective CEC-2021 Constrained Optimization Problems: Diversity Analysis and Validations DOI Creative Commons
M. Premkumar, Pradeep Jangir, B. Santhosh Kumar

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 84263 - 84295

Published: Jan. 1, 2021

In this paper, a new Multi-Objective Arithmetic Optimization Algorithm (MOAOA) is proposed for solving Real-World constrained Multi-objective Problems (RWMOPs). Such problems can be found in different fields, including mechanical engineering, chemical process and synthesis, power electronics systems. MOAOA inspired by the distribution behavior of main arithmetic operators mathematics. The multi-objective version formulated developed from recently introduced single-objective (AOA) through an elitist non-dominance sorting crowding distance-based mechanism. For performance evaluation MOAOA, set 35 RWMOPs five ZDT unconstrained are considered. fitness efficiency results obtained compared with four other state-of-the-art algorithms. addition, indicators, such as Hyper-Volume (HV), Spread (SD), Inverted Generational Distance (IGD), Runtime (RT), (GD), calculated rigorous feasibility study MOAOA. findings demonstrate superiority over algorithms high accuracy coverage across all objectives. This paper also considers Wilcoxon signed-rank test (WSRT) statistical investigation experimental study. coverage, diversity, computational cost, convergence achieved show its problems.

Language: Английский

Citations

141
Comparative analysis of the hybrid gazelle‐Nelder–Mead algorithm for parameter extraction and optimization of solar photovoltaic systems DOI Creative Commons
Serdar Ekinci, Davut İzci, Abdelazim G. Hussien

et al.

IET Renewable Power Generation, Journal Year: 2024, Volume and Issue: 18(6), P. 959 - 978

Published: Feb. 20, 2024

Abstract The pressing need for sustainable energy solutions has driven significant research in optimizing solar photovoltaic (PV) systems which is crucial maximizing conversion efficiency. Here, a novel hybrid gazelle‐Nelder–Mead (GOANM) algorithm proposed and evaluated. GOANM synergistically integrates the gazelle optimization (GOA) with Nelder–Mead (NM) algorithm, offering an efficient powerful approach parameter extraction PV models. This investigation involves thorough assessment of algorithm's performance across diverse benchmark functions, including unimodal, multimodal, fixed‐dimensional CEC2020 functions. Notably, consistently outperforms other approaches, demonstrating enhanced convergence speed, accuracy, reliability. Furthermore, application extended to single diode double models RTC France cell model Photowatt‐PWP201 module. experimental results demonstrate that approaches terms accurate estimation, low root mean square values, fast convergence, alignment data. These emphasize its role achieving superior efficiency renewable systems.

Language: Английский

Citations

24
Enhancing photovoltaic parameter estimation: integration of non-linear hunting and reinforcement learning strategies with golden jackal optimizer DOI Creative Commons

Chappani Sankaran Sundar Ganesh,

C. Kumar,

M. Premkumar

et al.

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

Published: Feb. 2, 2024

Abstract The advancement of Photovoltaic (PV) systems hinges on the precise optimization their parameters. Among numerous techniques, effectiveness each often rests inherent This research introduces a new methodology, Reinforcement Learning-based Golden Jackal Optimizer (RL-GJO). approach uniquely combines reinforcement learning with to enhance its efficiency and adaptability in handling various problems. Furthermore, incorporates an advanced non-linear hunting strategy optimize algorithm’s performance. proposed algorithm is first validated using 29 CEC2017 benchmark test functions five engineering-constrained design Secondly, rigorous testing PV parameter estimation datasets, including single-diode model, double-diode three-diode representative module, was carried out highlight superiority RL-GJO. results were compelling: root mean square error values achieved by RL-GJO markedly lower than those original other prevalent methods. synergy between GJO this facilitates faster convergence improved solution quality. integration not only improves performance metrics but also ensures more efficient process, especially complex scenarios. With average Freidman’s rank 1.564 for numerical engineering problems 1.742 problems, performing better peers. stands as reliable tool estimation. By seamlessly combining golden jackal optimizer, it sets optimization, indicating promising avenue future applications.

Language: Английский

Citations

23
Differential evolution algorithm featuring novel mutation combined with Newton-Raphson method for enhanced photovoltaic parameter extraction DOI

Charaf Chermite,

Moulay Rachid Douiri

Energy Conversion and Management, Journal Year: 2025, Volume and Issue: 326, P. 119468 - 119468

Published: Jan. 5, 2025

Language: Английский

Citations

3
A reinforcement learning-based ranking teaching-learning-based optimization algorithm for parameters estimation of photovoltaic models DOI
Haoyu Wang, Xiaobing Yu,

Yangchen Lu

et al.

Swarm and Evolutionary Computation, Journal Year: 2025, Volume and Issue: 93, P. 101844 - 101844

Published: Jan. 9, 2025

Language: Английский

Citations

2
Metaheuristic optimization algorithms for multi-area economic dispatch of power systems: part II—a comparative study DOI Creative Commons
Yan Wang, Guojiang Xiong

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(5)

Published: Feb. 14, 2025

Language: Английский

Citations

2
A novel hybrid approach combining Differentiated Creative Search with adaptive refinement for photovoltaic parameter extraction DOI

Charaf Chermite,

Moulay Rachid Douırı

Renewable Energy, Journal Year: 2025, Volume and Issue: unknown, P. 122764 - 122764

Published: Feb. 1, 2025

Language: Английский

Citations

2
MOPGO: A New Physics-Based Multi-Objective Plasma Generation Optimizer for Solving Structural Optimization Problems DOI Creative Commons
Sumit Kumar, Pradeep Jangir, Ghanshyam G. Tejani

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 84982 - 85016

Published: Jan. 1, 2021

This paper proposes a new Multi-Objective Plasma Generation Optimization (MOPGO) algorithm, and its non-dominated sorting mechanism is investigated for numerous challenging real-world structural optimization design problems. The (PGO) algorithm recently reported physics-based inspired by the generation process of plasma in which electron movement energy level are based on excitation modes, de-excitation, ionization processes. As search progresses, better balance between exploration exploitation has more significant impact results; thus, crowding distance feature incorporated proposed MOPGO algorithm. Also, posteriori method exercises strategy to preserve population diversity, crucial problem multi-objective meta-heuristic algorithms. In truss problems, minimization truss's mass maximization nodal displacement considered objective functions. contrast, elemental stress discrete cross-sectional areas assumed be behavior side constraints, respectively. usefulness solve complex problems validated eight truss-bar efficacy evaluated ten performance metrics. results demonstrate that achieves optimal solution with less computational complexity convergence, coverage, spread. Pareto fronts compared contrasted passing vehicle slime mould symbiotic organisms ant lion study will further supported external guidance at https://premkumarmanoharan.wixsite.com/mysite.

Language: Английский

Citations

78
Identification of Solar Photovoltaic Model Parameters Using an Improved Gradient-Based Optimization Algorithm With Chaotic Drifts DOI Creative Commons
M. Premkumar, Pradeep Jangir,

C. Ramakrishnan

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 62347 - 62379

Published: Jan. 1, 2021

When discussing the commercial applications of photovoltaic (PV) systems, one most critical problems is to estimate efficiency a PV system because current (I) – voltage (V) and power (P) characteristics are highly non-linear. It should be noted that manufacturer's datasheets do not have complete information on electrical equivalent parameters systems necessary for simulating an effective module. Compared conventional approaches, computational optimization global research strategies more acceptable as alternative parameter estimation solar modules. Recently, Gradient-based optimizer (GBO) reported solve engineering design problems. However, basic GBO algorithm stuck in local optima when handling complex non-linear In this sense, paper presents new technique called Chaotic-GBO (CGBO) derive modules while offering precise I-V P-V curves. To end, CGBO based chaotic generator obtain combined with algorithm. There five case studies considered validate performance proposed A quantitative qualitative evaluation reveals has improved results than other state-of-the-art algorithms terms accuracy robustness obtaining parameters. The average RMSE values runtime equal 9.8427E-04, 2.3700E-04, 2.4251E-03, 4.3524E-03 1.8349E-03, 18.44, 17.78, 18.18, 18.28 17.97, respectively. proved superiority over different selected algorithms. For future research, study will backed up external support at https://premkumarmanoharan.wixsite.com/mysite .

Language: Английский

Citations

77
Review on parameter estimation techniques of solar photovoltaic systems DOI Open Access

R. Venkateswari,

N. Rajasekar

International Transactions on Electrical Energy Systems, Journal Year: 2021, Volume and Issue: 31(11)

Published: Sept. 27, 2021

Beyond meeting power demand, switching to solar energy especially photovoltaic (PV) offers many advantages like modularity, minimal maintenance, pollution free, and zero noise. Yet, its cell modeling is critical in design, simulation analysis, evaluation, control of PV system; most importantly tap maximum potential. However, precise complicated by nonlinearity, presence large unknown model parameter, absence a unique method. Since number parameters involved directly related accuracy, efficiency; determination values assume high priority. Besides, application meta-heuristic algorithms via numerical extraction popular as it suits for any cell/module types operating conditions. existence have drawn attention toward assessment each method based on merits, demerits, suitability/ability parameter estimation problem, complexity involved. Hence, few authors reviewed the subject estimation. But existing reviews focused comparative analysis analytical approaches, models, methods extraction. Thus, lack comprehensive different objective function, environmental conditions, cumulative selective set algorithm efficiency. Therefore, this work optimization presented focusing (a) function used, (b) type, (c) employed extraction, (d) technology. Further, provides various modules used validation, comparisons made with methods, disadvantages associated respect platform, at STC, varying irradiance In addition, evaluation specific also carried out. Thus explores display characteristics techniques serve be single reference researchers working field

Language: Английский

Citations

77