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Frequency-Based Optimization of Truss Dome Structures Using Ant Colony Optimization (\({{\varvec{A}}{\varvec{C}}{\varvec{O}}}_{\mathbb{R}}\)) with Multi-trail Pheromone Memory

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Applications of Ant Colony Optimization and its Variants

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

This study focuses on the frequency-based optimization of truss dome structures using enhanced ant colony optimization algorithms for the continuous domain (\({ACO}_{\mathbb{R}}\)). The purpose is to optimize the size or size/shape of the truss structure by considering the frequency constraints. To improve the performance of the \({ACO}_{\mathbb{R}}\) algorithm, an operator, namely, multi-trail pheromone memory, is incorporated. The objective of this operator is to enhance the algorithm's capabilities for both exploration and exploitation. Two truss domes, 52-bar and 120-bar trusses, are used to evaluate the performance of the algorithm. The results achieved from the enhanced \({ACO}_{\mathbb{R}}\) algorithms are compared with the results achieved from the standard \({ACO}_{\mathbb{R}}\). The comparative investigation demonstrates the efficacy of the enhanced \({ACO}_{\mathbb{R}}\) algorithms in achieving better optimization results.

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Authors and Affiliations

  1. Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Zanjan, Iran

    Salar Farahmand-Tabar

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  1. Department of Computer Science and Engineering, Techno International New Town, New Town, West Bengal, India

    Nilanjan Dey

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Farahmand-Tabar, S. (2024). Frequency-Based Optimization of Truss Dome Structures Using Ant Colony Optimization (\({{\varvec{A}}{\varvec{C}}{\varvec{O}}}_{\mathbb{R}}\)) with Multi-trail Pheromone Memory. In: Dey, N. (eds) Applications of Ant Colony Optimization and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-99-7227-2_11

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