Fishing cat optimizer: a novel metaheuristic technique DOI
Xiaowei Wang

Engineering Computations, Год журнала: 2025, Номер unknown

Опубликована: Фев. 10, 2025

Purpose The fishing cat's unique hunting strategies, including ambush, detection, diving and trapping, inspired the development of a novel metaheuristic optimization algorithm named Fishing Cat Optimizer (FCO). purpose this paper is to introduce FCO, offering fresh perspective on demonstrating its potential for solving complex problems. Design/methodology/approach FCO structures process into four distinct phases. Each phase incorporates tailored search strategy enrich diversity population attain an optimal balance between extensive global exploration focused local exploitation. Findings To assess efficacy algorithm, we conducted comparative analysis with state-of-the-art algorithms, COA, WOA, HHO, SMA, DO ARO, using test suite comprising 75 benchmark functions. findings indicate that achieved results 88% functions, whereas SMA which ranked second, excelled only 21% Furthermore, secured average ranking 1.2 across sets CEC2005, CEC2017, CEC2019 CEC2022, superior convergence capability robustness compared other comparable algorithms. Research limitations/implications Although performs excellently in single-objective problems constrained problems, it also has some shortcomings defects. First, structure relatively there are many parameters. value parameters certain impact Second, computational complexity high. When high-dimensional takes more time than algorithms such as GWO WOA. Third, although multimodal rarely obtains theoretical solution when combinatorial Practical implications applied five common engineering design Originality/value This innovatively proposes mimics mechanisms cats, strategies lurking, perceiving, rapid precise trapping. These abstracted closely connected iterative stages, corresponding in-depth exploration, multi-dimensional fine developmental localized refinement contraction search. enables efficient fine-tuning environments, significantly enhancing algorithm's adaptability efficiency.

Язык: Английский

Experimental investigation of mechanical properties of PLA, ABS, and PETG 3-d printing materials using fused deposition modeling technique DOI

Mehmet Kopar,

Ali Rıza Yıldız

Materials Testing, Год журнала: 2023, Номер 65(12), С. 1795 - 1804

Опубликована: Сен. 7, 2023

Abstract In recent years, there has been a logarithmic interest in three-dimensional printing technologies. This technique made it possible to make more intricately shaped parts of superior quality, allowing for use variety industries, including aircraft, automobiles, and ships. study characterized the materials assessed mechanical features PLA, PETG, ABS generated at various raster angles. The strength ratios have found fluctuate when angles change. PLA created picture angle 45° had maximum tensile strength. material with shown best energy absorption, performance compressive When bending was evaluated, that samples 0–90° greatest value. SEM micrographs were obtained, test used examine fracture behavior materials. As result, using can values from one another.

Язык: Английский

Процитировано

37
A novel hybrid Fick’s law algorithm-quasi oppositional–based learning algorithm for solving constrained mechanical design problems DOI
Pranav Mehta, Betül Sultan Yıldız, Sadiq M. Sait

и другие.

Materials Testing, Год журнала: 2023, Номер 65(12), С. 1817 - 1825

Опубликована: Сен. 13, 2023

Abstract In this article, a recently developed physics-based Fick’s law optimization algorithm is utilized to solve engineering challenges. The performance of the further improved by incorporating quasi-oppositional–based techniques at programming level. modified was applied optimize rolling element bearing system, robot gripper, planetary gear and hydrostatic thrust bearing, along with shape vehicle bracket system. Accordingly, realizes promising statistical results compared rest well-known algorithms. Furthermore, required number iterations comparatively less attain global optimum solution. Moreover, deviations in were least even when other optimizers provided better or more competitive results. This being said that can be adopted for critical wide range industrial real-world challenges optimization.

Язык: Английский

Процитировано

25
Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components DOI
Sadiq M. Sait, Pranav Mehta, Nantiwat Pholdee

и другие.

Materials Testing, Год журнала: 2024, Номер unknown

Опубликована: Авг. 30, 2024

Abstract This paper introduces and investigates an enhanced Partial Reinforcement Optimization Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory to efficiently solve complex engineering optimization problems. The proposed combines the (PROA) with quasi-oppositional learning approach improve performance of pure PROA. E-PROA was applied five distinct design components: speed reducer design, step-cone pulley weight optimization, economic cantilever beams, coupling bolted rim vehicle suspension arm An artificial neural network as metamodeling is used obtain equations for shape optimization. Comparative analyses other benchmark algorithms, such ship rescue algorithm, mountain gazelle optimizer, cheetah demonstrated superior in terms convergence rate, solution quality, computational efficiency. results indicate that holds excellent promise technique addressing

Язык: Английский

Процитировано

9
Nonlinear FOPID controller design for pressure regulation of steam condenser via improved metaheuristic algorithm DOI Creative Commons
Sarah A. Alzakari, Davut İzci,

Serdar Ekinci

и другие.

PLoS ONE, Год журнала: 2024, Номер 19(9), С. e0309211 - e0309211

Опубликована: Сен. 19, 2024

Shell and tube heat exchangers are pivotal for efficient transfer in various industrial processes. Effective control of these structures is essential optimizing energy usage ensuring system reliability. In this regard, study focuses on adopting a fractional-order proportional-integral-derivative (FOPID) controller shell exchanger. The novelty work lies the utilization an enhanced version cooperation search algorithm (CSA) FOPID tuning, offering novel approach to optimization. optimizer (en-CSA) integrates randomization operator, linear function, adaptive p-best mutation integrated with original CSA. Through rigorous testing CEC2020 benchmark functions, en-CSA demonstrates robust performance, surpassing other optimization algorithms. Specifically, achieves average convergence rate improvement 23% enhancement solution accuracy by 17% compared standard CSAs. Subsequently, applied optimize steam condenser pressure regulation, crucial aspect exchanger operation. Nonlinear comparative analysis contemporary algorithms confirms en-CSA’s superiority, achieving up 11% faster settling time 55% reduced overshooting. Additionally, improves steady-state error 8% enhances overall stability margin 12%.

Язык: Английский

Процитировано

9
Grid-connected desalination plant economic management powered by renewable resources utilizing Niching Chimp Optimization and hunger game search algorithms DOI

Yuanshuo Guo,

Yassine Bouteraa, Mohammad Khishe

и другие.

Sustainable Computing Informatics and Systems, Год журнала: 2024, Номер 42, С. 100976 - 100976

Опубликована: Фев. 2, 2024

Язык: Английский

Процитировано

8
Optimum design of a composite drone component using slime mold algorithm DOI

Mehmet Kopar,

Ali Rıza Yıldız, Betül Sultan Yıldız

и другие.

Materials Testing, Год журнала: 2023, Номер 65(12), С. 1857 - 1864

Опубликована: Сен. 22, 2023

Abstract Composite materials have a wide range of applications in many industries due to their manufacturability, high strength values, and light filling. The sector where composite are mostly used is the aviation industry. Today, as result development systems, drones started be actively used, studies carried out mitigate them. In this study, subcarrier part, which part drone, was designed using glass carbon fiber–reinforced materials. Using data obtained at end analysis, stacking angle with optimal displacement stress value determined by genetic algorithm (GA), gray wolf (GWO), slime mold optimization (SMO) techniques order develop carrier minimum more than 60 MPa. As optimization, it that artificial intelligence algorithms could effectively determining materials, optimum values were algorithm.

Язык: Английский

Процитировано

16
Experimental and numerical investigation of crash performances of additively manufactured novel multi-cell crash box made with CF15PET, PLA, and ABS DOI

Mehmet Kopar,

Ali Rıza Yıldız

Materials Testing, Год журнала: 2024, Номер 66(9), С. 1510 - 1518

Опубликована: Авг. 13, 2024

Abstract In this study, a novel multi-cell crash box was designed and produced using 15 % short carbon fiber reinforced polyethylene terephthalate (CF15PET), polylactic acid (PLA), acrylonitrile butadiene styrene (ABS) filaments one of the additive manufacturing methods, melt deposition method (FDM). All structures’ maximum force energy absorption performances have been investigated. As result test, it determined that box, which best meets high folding properties, expected features in boxes, has parts manufactured ABS CF15PET materials. According to test result, found is 11 higher than approximately 4.5 PLA. It response value 5 12 materials can be used boxes form an idea about design by designing analyzing finite element programs.

Язык: Английский

Процитировано

7
The application of project management methodology in the training of college students' innovation and entrepreneurship ability under sustainable education DOI Creative Commons
Hailing Wei,

Ailing Ding,

Zhiqiang Gao

и другие.

Systems and Soft Computing, Год журнала: 2024, Номер 6, С. 200073 - 200073

Опубликована: Янв. 25, 2024

With the rapid development of society and rise knowledge economy, cultivating innovation entrepreneurship abilities college students has gradually become an important task higher education. However, in current educational environment, cultivation among faces a series issues, such as disconnect between practice, singularity training methods. To address these analysis existing education was conducted using project management method. A combination model for constructed Analytic Hierarchy Process (AHP) entropy Considering that talent belongs to complex nonlinear solving problem, advanced ABC-BP adopted handle linear data problem model. Among them, Back Propagation (BP) used train refine parameters model, explore optimal factors. BP is prone local convergence parameterization problems, Artificial Bee Colony (ABC) algorithm optimized improved effect enhanced application abilities. In test compared with classic Particle Swarm Optimization (PSO) proposed had lower overall RMSE, greater optimization precision faster speed terms results. Compared PSO increased by 14%. The selected solve According solution results, highest comprehensive score scheme 1 0.57, finally best training. This study reference significance innovative entrepreneurial talents China. Through AHP methods, effectiveness can be improved, more cultivated meet needs rapidly developing economy.

Язык: Английский

Процитировано

6
A spherical evolution algorithm with two-stage search for global optimization and real-world problems DOI
Yirui Wang,

Zonghui Cai,

Lijun Guo

и другие.

Information Sciences, Год журнала: 2024, Номер 665, С. 120424 - 120424

Опубликована: Март 6, 2024

Язык: Английский

Процитировано

5
Marathon runner algorithm: theory and application in mathematical, mechanical and structural optimization problems DOI
Ali Mortazavi

Materials Testing, Год журнала: 2024, Номер 66(8), С. 1267 - 1291

Опубликована: Май 22, 2024

Abstract This study proposes a novel human-inspired metaheuristic search algorithm called marathon runner algorithm. method mimics competitive behaviors observed in real runners through mathematical modeling. Unlike classical elitist algorithms that prioritize position of the best agent, introduces concept vision point. point considers quality entire population, not just leader. By guiding population towards point, risk getting trapped local optima is reduced. A two-part evaluation was conducted to thoroughly assess capabilities First, it tested against set unconstrained benchmark functions and algorithm’s quantitative attributes, such as complexity, accuracy, stability, diversity, sensitivity, convergence rate are analyzed. Subsequently, applied mechanical structural optimization problems with both continuous discrete variables. application demonstrated effectiveness solving practical engineering challenges constraints. The outcomes compared those obtained by six other well-established techniques. results indicate yields promising solutions for mathematical, mechanical, problems.

Язык: Английский

Процитировано

5