Journal of Network and Computer Applications, Год журнала: 2023, Номер 214, С. 103617 - 103617
Опубликована: Март 2, 2023
Язык: Английский
Knowledge-Based Systems, Год журнала: 2023, Номер 268, С. 110454 - 110454
Опубликована: Март 11, 2023
Язык: Английский
Процитировано
270
Knowledge-Based Systems, Год журнала: 2023, Номер 282, С. 111081 - 111081
Опубликована: Окт. 18, 2023
Язык: Английский
Процитировано
93
Computer Methods in Applied Mechanics and Engineering, Год журнала: 2023, Номер 415, С. 116200 - 116200
Опубликована: Июль 10, 2023
Язык: Английский
Процитировано
79
Alexandria Engineering Journal, Год журнала: 2023, Номер 68, С. 141 - 180
Опубликована: Янв. 18, 2023
The use of metaheuristics is one the most encouraging methodologies for taking care real-life problems. Bald eagle search (BES) algorithm latest swarm-intelligence metaheuristic inspired by intelligent hunting behavior bald eagles. In recent research works, BES has performed reasonably well over a wide range application areas such as chemical engineering, environmental science, physics and astronomy, structural modeling, global optimization, engineering design, energy efficiency, etc. However, it still lacks adequate searching efficiency tendency to stuck in local optima which affects final outcome. This paper introduces modified (mBES) that removes shortcomings original incorporating three improvements; Opposition-based learning (OBL), Chaotic Local Search (CLS), Transition & Pharsor operators. OBL embedded different phases standard viz. initial population, selecting, space, swooping update positions individual solutions strengthen exploration, CLS used enhance position best agent will lead enhancing all individuals, operators help provide sufficient exploration–exploitation trade-off. mBES initially evaluated with 29 CEC2017 10 CEC2020 optimization benchmark functions. addition, practicality tested real-world feature selection problem five design Results are compared against number classical algorithms using statistical metrics, convergence analysis, box plots, Wilcoxon rank sum test. case composite test functions F21-F30, wins 70% cases, whereas rest functions, generates good results 65% cases. proposed produces performance 55% 45% generated competitive results. On other hand, problems, among algorithms. problem, also showed competitiveness observations problems show superiority robustness baseline metaheuristics. It can be safely concluded improvements suggested proved effective making enough solve variety
Язык: Английский
Процитировано
64
Materials Testing, Год журнала: 2023, Номер 65(8), С. 1230 - 1236
Опубликована: Июнь 29, 2023
Abstract Thermal system optimization is always a challenging task due to several constraints and critical concepts of thermo-hydraulic aspects. Heat exchangers are one those devices that widely adopted in thermal industries for various applications such as cryogenics, heat recovery, transfer applications. According the flow configurations enhancement fins, classified plate-fin exchangers, shell tube tube-fin exchangers. This article addresses economic challenge using cheetah (CO) algorithm. The design variables were optimized CO algorithm, statistical results compared with eight well-established algorithms. study revealed algorithm prominent terms realizing minimizing overall cost exchanger 100 % success rate. Furthermore, suggests adopting optimizer solving challenges different fields.
Язык: Английский
Процитировано
54
Biomimetics, Год журнала: 2023, Номер 8(5), С. 386 - 386
Опубликована: Авг. 24, 2023
In this research article, we uphold the principles of No Free Lunch theorem and employ it as a driving force to introduce an innovative game-based metaheuristic technique named Golf Optimization Algorithm (GOA). The GOA is meticulously structured with two distinctive phases, namely, exploration exploitation, drawing inspiration from strategic dynamics player conduct observed in sport golf. Through comprehensive assessments encompassing fifty-two objective functions four real-world engineering applications, efficacy rigorously examined. results optimization process reveal GOA’s exceptional proficiency both exploitation strategies, effectively striking harmonious equilibrium between two. Comparative analyses against ten competing algorithms demonstrate clear statistically significant superiority across spectrum performance metrics. Furthermore, successful application intricate energy commitment problem, considering network resilience, underscores its prowess addressing complex challenges. For convenience community, provide MATLAB implementation codes for proposed methodology, ensuring accessibility facilitating further exploration.
Язык: Английский
Процитировано
51
Journal of Materials Research and Technology, Год журнала: 2023, Номер 23, С. 4551 - 4565
Опубликована: Фев. 18, 2023
Recent studies highlight the feasibility of using activated alkali cement (AAC) as a substitute for Portland cement. In this context, objective article is to evaluate influence type curing on mechanical properties ACC based blast furnace slag. For this, cylindrical specimens measuring 50 × 100 mm were made slag by sodium hydroxide with different mass concentrations (2.5–15%). Normal at room temperature, thermal 65 °C, solution distilled water (saturated curing), hydrated lime (lime curing) and (sodium compound carried out. The compressive strength results 7 28 days indicate that AAC presents superior behavior OPC. Regarding mechanisms, most advantageous curing, which promoted greater energy, in solution, prevented loss alkaline ions from AAC. these types healing, there was formation tobermorite hydrotalcite, an increase activation rates, evidenced XRD, FTIR TDG. situations inefficient such saturated ettringite efflorescence formed, impairing material. It concluded best cure or depending Na2O concentration.
Язык: Английский
Процитировано
47
Knowledge-Based Systems, Год журнала: 2023, Номер 275, С. 110679 - 110679
Опубликована: Июнь 5, 2023
Язык: Английский
Процитировано
44
Knowledge-Based Systems, Год журнала: 2024, Номер 295, С. 111737 - 111737
Опубликована: Апрель 12, 2024
This study proposes a novel artificial protozoa optimizer (APO) that is inspired by in nature. The APO mimics the survival mechanisms of simulating their foraging, dormancy, and reproductive behaviors. was mathematically modeled implemented to perform optimization processes metaheuristic algorithms. performance verified via experimental simulations compared with 32 state-of-the-art Wilcoxon signed-rank test performed for pairwise comparisons proposed algorithms, Friedman used multiple comparisons. First, tested using 12 functions 2022 IEEE Congress on Evolutionary Computation benchmark. Considering practicality, solve five popular engineering design problems continuous space constraints. Moreover, applied multilevel image segmentation task discrete experiments confirmed could provide highly competitive results problems. source codes Artificial Protozoa Optimizer are publicly available at https://seyedalimirjalili.com/projects https://ww2.mathworks.cn/matlabcentral/fileexchange/162656-artificial-protozoa-optimizer.
Язык: Английский
Процитировано
39
PLoS ONE, Год журнала: 2024, Номер 19(8), С. e0308474 - e0308474
Опубликована: Авг. 19, 2024
This research article presents the Multi-Objective Hippopotamus Optimizer (MOHO), a unique approach that excels in tackling complex structural optimization problems. The (HO) is novel meta-heuristic methodology draws inspiration from natural behaviour of hippos. HO built upon trinary-phase model incorporates mathematical representations crucial aspects Hippo's behaviour, including their movements aquatic environments, defense mechanisms against predators, and avoidance strategies. conceptual framework forms basis for developing multi-objective (MO) variant MOHO, which was applied to optimize five well-known truss structures. Balancing safety precautions size constraints concerning stresses on individual sections constituent parts, these problems also involved competing objectives, such as reducing weight structure maximum nodal displacement. findings six popular methods were used compare results. Four industry-standard performance measures this comparison qualitative examination finest Pareto-front plots generated by each algorithm. average values obtained Friedman rank test analysis unequivocally showed MOHO outperformed other resolving significant quickly. In addition finding preserving more Pareto-optimal sets, recommended algorithm produced excellent convergence variance objective decision fields. demonstrated its potential navigating objectives through diversity analysis. Additionally, swarm effectively visualize MOHO's solution distribution across iterations, highlighting superior behaviour. Consequently, exhibits promise valuable method issues.
Язык: Английский
Процитировано
35