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Journal ArticleDOI

Design optimization of real world steel space frames using artificial bee colony algorithm with Levy flight distribution

TLDR
Optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC and its solution is obtained by using enhanced artificial bee colony algorithm by adding Levy flight distribution in the search of scout bees.
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This article is published in Advances in Engineering Software.The article was published on 2016-02-01. It has received 109 citations till now. The article focuses on the topics: Artificial bee colony algorithm & Bees algorithm.

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Citations
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A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems

TL;DR: The convergence speed of ASO is improved using chaotic maps and Levy flight random walk and the proposed hybrid algorithm is hybridized with the tree-seed algorithm to improve exploration and exploitation capabilities and make a proper balance between them.
Journal ArticleDOI

Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

TL;DR: In this paper, a new version of a biogeography-based optimization algorithm with Levy flight distribution (LFBBO) is introduced and used for the optimum design of reinforced concrete cantilever retaining walls under seismic loading.
Journal ArticleDOI

SelEQ: An advanced ground motion record selection and scaling framework

TL;DR: SelEQ, a fully integrated framework that implements state-of-the art procedures for ground motion record selection and scaling, makes use of the Adaptive Harmony Search meta-heuristic optimization algorithm in order to significantly minimize computational cost and analysis time, whilst still meeting the imposed selection constraints.
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Improving ant colony optimization algorithm with epsilon greedy and Levy flight

TL;DR: According to the computational experiments using standard TSPLIB instances, greedy–Levy ACO outperforms max–min ACO and other latest TSP solvers, which demonstrates the effectiveness of the proposed methodology.
References
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Journal ArticleDOI

A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

TL;DR: Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm that is used for optimizing multivariable functions and the results showed that ABC outperforms the other algorithms.
Proceedings ArticleDOI

Cuckoo Search via Lévy flights

TL;DR: A new meta-heuristic algorithm, called Cuckoo Search (CS), is formulated, based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour ofSome birds and fruit flies, for solving optimization problems.
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On the performance of artificial bee colony (ABC) algorithm

TL;DR: The simulation results show that the performance of ABC algorithm is comparable to those of differential evolution, particle swarm optimization and evolutionary algorithm and can be efficiently employed to solve engineering problems with high dimensionality.
Journal ArticleDOI

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

TL;DR: This work presents a comprehensive survey of the advances with ABC and its applications and it is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.