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Harris hawks optimization: Algorithm and applications [PDF]
Future Generation Computer Systems, 2019 Abstract In this paper, a novel population-based, nature-inspired optimization paradigm is proposed, which is called Harris Hawks Optimizer (HHO). The main inspiration of HHO is the cooperative behavior and chasing style of Harris’ hawks in nature called surprise pounce.
Ali Asghar Heidari +2 more
exaly +5 more sources
Nonlinear-based Chaotic Harris Hawks Optimizer: Algorithm and Internet of Vehicles application [PDF]
Applied Soft Computing Journal, 2021 Abstract Harris Hawks Optimizer (HHO) is one of the many recent algorithms in the field of metaheuristics. The HHO algorithm mimics the cooperative behavior of Harris Hawks and their foraging behavior in nature called surprise pounce. HHO benefits from a small number of controlling parameters setting, simplicity of implementation, and a high level of
Kayhan Zrar Ghafoor +2 more
exaly +6 more sources
A hybrid Harris hawks-moth-flame optimization algorithm including fractional-order chaos maps and evolutionary population dynamics [PDF]
Advances in Engineering Software, 2021 This paper proposes a modified version of a contemporary metaheuristic named Harris Hawks Optimizer (HHO) that mimics the foraging strategies used by Harris hawks. It is first argued that exploration ability of HHO is weaker than its exploitation.
Dalia Yousri +2 more
exaly +2 more sources
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Compact Harris Hawks Optimization Algorithm
2021 40th Chinese Control Conference (CCC), 2021The intelligent optimization algorithm performs well in solving complex optimization problems in engineering. However, the intelligent optimization algorithm usually takes long execution time and large memory usage, which is not suitable for the engineering with limited hardware conditions.
Zhihao Yu, Jialu Du, Guangqiang Li
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A Novel Ensemble of Arithmetic Optimization Algorithm and Harris Hawks Optimization for Solving Industrial Engineering Optimization Problems [PDF]
Machines, 2022 Recently, numerous new meta-heuristic algorithms have been proposed for solving optimization problems. According to the Non-Free Lunch theorem, we learn that no single algorithm can solve all optimization problems.
Yongbai Sha
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Modified Harris Hawks Optimization Algorithm for Global Optimization Problems
Arabian Journal for Science and Engineering, 2020The Harris hawks optimization algorithm (HHO) is a novel swarm-based meta-heuristic algorithm. In this study, a modified Harris hawks optimization algorithm (MHHO) is proposed to enhance the searching performance of the conventional HHO. Past studies have revealed that different adjustment strategies of important variables in meta-heuristic algorithm ...
Po-Chou Shih, Xizhao Zhou
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An improved Harris Hawks Optimization algorithm for continuous and discrete optimization problems
Engineering Applications of Artificial Intelligence, 2022Harris Hawks Optimization (HHO) is a population-based meta-heuristic optimization algorithm that has been used for the solution of test functions and real-world problems by many researchers. However, HHO has a premature convergence problem. The main motive of the novel approach in this paper is that the performance of an MHA could be improved by ...
Harun Gezici, Haydar Livatyali
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Passive vehicle suspension system optimization using Harris Hawk Optimization algorithm
Mathematics and Computers in Simulation, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mohamed Issa, Anas Samn
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An efficient harris hawk optimization algorithm for solving the travelling salesman problem
Cluster Computing, 2021Travelling Salesman Problem (TSP) is an Np-Hard problem, for which various solutions have been offered so far. Using the Harris Hawk Optimization (HHO) algorithm, this paper presented a new method that uses random-key encoding to generate a tour.
Farhad Soleimanian Gharehchopogh +1 more
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Harris Hawks Optimization Algorithm for Waveguide Filter Designs
2020 IEEE Asia-Pacific Microwave Conference (APMC), 2020We apply a novel algorithm, Harris Hawks optimization (HHO), to the optimization problem of waveguide filters. In order to investigate the efficiency, particle swarm optimization(PSO), differential evolution(DE), and self-adaptive differential optimization(SaDE) are considered to optimize a fourth-order dual-mode waveguide filter as well.
Pei-Wen Shu, Qing-Xin Chu, Jian-Ye Mai
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