An efficient hybrid approach based on Harris Hawks optimization and imperialist competitive algorithm for structural optimization

In this paper, a new hybrid algorithm is introduced, combining two Harris Hawks Optimizer (HHO) and the Imperialist Competitive Algorithm (ICA) to achieve a better search strategy. HHO is a new population-based, nature-inspired optimization algorithm that mimics Harris Hawks cooperative behavior and...

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Published inEngineering with computers Vol. 38; no. Suppl 2; pp. 1555 - 1583
Main Authors Kaveh, A., Rahmani, P., Eslamlou, A. Dadras
Format Journal Article
LanguageEnglish
Published London Springer London 01.06.2022
Springer Nature B.V
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Abstract In this paper, a new hybrid algorithm is introduced, combining two Harris Hawks Optimizer (HHO) and the Imperialist Competitive Algorithm (ICA) to achieve a better search strategy. HHO is a new population-based, nature-inspired optimization algorithm that mimics Harris Hawks cooperative behavior and chasing style in nature called surprise pounce HHO. It is a robust algorithm in exploitation, but has an unfavorable performance in exploring the search space, while ICA has a better performance in exploration; thus, combining these two algorithms produces an effective hybrid algorithm. The hybrid algorithm is called Imperialist Competitive Harris Hawks Optimization (ICHHO). The proposed hybrid algorithm's effectiveness is examined by comparing other nature-inspired techniques, 23 mathematical benchmark problems, and several well-known structural engineering problems. The results successfully indicate the proposed hybrid algorithm's competitive performance compared to HHO, ICA, and some other well-established algorithms.
AbstractList In this paper, a new hybrid algorithm is introduced, combining two Harris Hawks Optimizer (HHO) and the Imperialist Competitive Algorithm (ICA) to achieve a better search strategy. HHO is a new population-based, nature-inspired optimization algorithm that mimics Harris Hawks cooperative behavior and chasing style in nature called surprise pounce HHO. It is a robust algorithm in exploitation, but has an unfavorable performance in exploring the search space, while ICA has a better performance in exploration; thus, combining these two algorithms produces an effective hybrid algorithm. The hybrid algorithm is called Imperialist Competitive Harris Hawks Optimization (ICHHO). The proposed hybrid algorithm's effectiveness is examined by comparing other nature-inspired techniques, 23 mathematical benchmark problems, and several well-known structural engineering problems. The results successfully indicate the proposed hybrid algorithm's competitive performance compared to HHO, ICA, and some other well-established algorithms.
Author Kaveh, A.
Rahmani, P.
Eslamlou, A. Dadras
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  surname: Eslamlou
  fullname: Eslamlou, A. Dadras
  organization: School of Civil Engineering, Iran University of Science and Technology
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Keywords Benchmark functions
Harris Hawks optimization
Imperialist competitive algorithm
Hybrid algorithm
Truss structures
Language English
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Snippet In this paper, a new hybrid algorithm is introduced, combining two Harris Hawks Optimizer (HHO) and the Imperialist Competitive Algorithm (ICA) to achieve a...
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SubjectTerms Bombings
Business competition
CAE) and Design
Calculus of Variations and Optimal Control; Optimization
Civil engineering
Classical Mechanics
Competition
Computer Science
Computer-Aided Engineering (CAD
Control
Evolution
Evolutionary algorithms
Foraging behavior
Genetic algorithms
Math. Applications in Chemistry
Mathematical and Computational Engineering
Optimization
Original Article
Population
Robustness (mathematics)
Search methods
Structural engineering
Systems Theory
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Title An efficient hybrid approach based on Harris Hawks optimization and imperialist competitive algorithm for structural optimization
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