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| 1 | Archery Algorithm:A Novel Stochastic Optimization Algorithm for Solving Optimization Problems显示文摘Finding a suitable solution to an optimization problem designed in science is a major challenge.Therefore,these must be addressed utilizing proper approaches.Based on a random search space,optimization algorithms can find acceptable solutions to problems.Archery Algorithm(AA)is a new stochastic approach for addressing optimization problems that is discussed in this study.The fundamental idea of developing the suggested AA is to imitate the archer’s shooting behavior toward the target panel.The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the archer.The AA is mathematically described,and its capacity to solve optimization problems is evaluated on twenty-three distinct types of objective functions.Furthermore,the proposed algorithm’s performance is compared vs.eight approaches,including teaching-learning based optimization,marine predators algorithm,genetic algorithm,grey wolf optimization,particle swarm optimization,whale optimization algorithm,gravitational search algorithm,and tunicate swarm algorithm.According to the simulation findings,the AA has a good capacity to tackle optimization issues in both unimodal and multimodal scenarios,and it can give adequate quasi-optimal solutions to these problems.The analysis and comparison of competing algorithms’performance with the proposed algorithm demonstrates the superiority and competitiveness of the AA. | Fatemeh Ahmadi Zeidabadi Mohammad Dehghani Pavel Trojovsky Štěpán Hubálovsky Victor Leiva Gaurav Dhiman | 2022 | Computers, Materials & Continua2022，，7： | 2 |
| 2 | Axial mode helix antenna with exponential spacing显示文摘 | CHEN C H YUNG E K N HUB J | 2007 | Mi crowave and Optical Technology Letters2007，49，7： | 1 |
| 3 | ICP-AES determination of trace rare earth elements in environmental and food samples by on-line separation and preconcentration with acetylacetone- modified silica gel using microcolumn 显示文摘 | ZHANG N HUANG C Z HUB | 2007 | Analytical Sciences2007，23，8： | 1 |
| 4 | Time-division multiplexing by a photoconducting antenna array显示文摘 | FROBERG N M HUB B ZHANG X C | 1991 | Applied Physics Letter1991，59，： | 1 |
| 5 | Generation of tunable narrow band THz radiation from large aperture photoconducting antennas显示文摘 | WELING A S HUB B FROBERG N M | 1994 | Appl Phys Lett1994，66，： | 1 |
| 6 | DNA microarray technology reveals similar gene expression patterns in rats with vitamin A deficiency and chemically induced colitis 显示文摘 | Talia N Peijnenburg A Hub P | 2002 | J Nutr2002，132，8： | 1 |
| 7 | A zinc transition layer in electroless nickel plating 显示文摘 | CHEN J L YU G HUB N | 2006 | Surface and Coatings Technology2006，201，34： | 1 |
| 8 | From dissymmetrical mononuclear entities to centrosymmetrical heterotrinuclear complex with 2D supramolecular structure: synthesis, characterization, crystal structure, and magnetic properties显示文摘 | TAO R J ZANG S Q HUB N H | 2003 | Inorganica Chimica Acta2003，353，： | 1 |
| 9 | Scattering by conducting sphere coated with chiral media显示文摘 | YUNG E K N HUB J | 2002 | Micro Opt Tech Lett2002，35，4： | 1 |
| 10 | Preparation of Ag/ TiO2/Si02 films via photo - assisted deposition and ad- sorptive self- assembly for catalytic bactericidal appli- cation显示文摘 | Xi B J Chu X N Hub J Y | 2014 | Applied Surface Science2014，311，： | 1 |
| 11 | Electrochemical behaviors of the magnesium alloy substrates in various pretreatment solutions 显示文摘 | ZHU Y P YU G HUB N | 2010 | Applied Surface Science2010，256，9： | 1 |
| 12 | A zinc transition layer in electroless nickel plating 显示文摘 | CHEN Y L YU G HUB N LIU Z YE L Y WANG Z F | 2006 | Surface and Coatings Technology2006，201，34： | 1 |
| 13 | SSABA:Search Step Adjustment Based Algorithm显示文摘Finding the suitable solution to optimization problems is a fundamental challenge in various sciences.Optimization algorithms are one of the effective stochastic methods in solving optimization problems.In this paper,a new stochastic optimization algorithm called Search StepAdjustment Based Algorithm(SSABA)is presented to provide quasi-optimal solutions to various optimization problems.In the initial iterations of the algorithm,the step index is set to the highest value for a comprehensive search of the search space.Then,with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer to the global optimal,the step index is reduced to reach the minimum value at the end of the algorithm implementation.SSABA is mathematically modeled and its performance in optimization is evaluated on twenty-three different standard objective functions of unimodal and multimodal types.The results of optimization of unimodal functions show that the proposed algorithm SSABA has high exploitation power and the results of optimization of multimodal functions show the appropriate exploration power of the proposed algorithm.In addition,the performance of the proposed SSABA is compared with the performance of eight well-known algorithms,including Particle Swarm Optimization(PSO),Genetic Algorithm(GA),Teaching-Learning Based Optimization(TLBO),Gravitational Search Algorithm(GSA),Grey Wolf Optimization(GWO),Whale Optimization Algorithm(WOA),Marine Predators Algorithm(MPA),and Tunicate Swarm Algorithm(TSA).The simulation results show that the proposed SSABA is better and more competitive than the eight compared algorithms with better performance. | Fatemeh Ahmadi Zeidabadi Ali Dehghani Mohammad Dehghani Zeinab Montazeri Stepán Hubálovsky Pavel Trojovsky Gaurav Dhiman | 2022 | Computers, Materials & Continua2022，，6： | 0 |
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