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Article
Publication date: 18 January 2013

Victor V. Klemas

The purpose of this paper is to acquaint a wide audience of readers with some of the unique remote sensing and navigation capabilities of animals.

Abstract

Purpose

The purpose of this paper is to acquaint a wide audience of readers with some of the unique remote sensing and navigation capabilities of animals.

Design/methodology/approach

Biomimetic comparison of remote sensors evolved by animals and sensors designed by man. The study and comparison includes thermal infrared sensors used by snakes, echolocation used by bats and dolphins, and navigation methods used by birds. Countermeasures used by prey to avoid capture are also considered.

Findings

Some animals have remote sensing and navigation capabilities that are considerably more efficient than those provided by the human body or designed by man.

Practical implications

Sensor designers may be encouraged to use the biometic approach in the design of new sensors.

Social implications

The paper provides a better understanding of animal behaviour, especially their unique abilities to remotely sense, echolocate and navigate with high accuracy over considerable distances.

Originality/value

The paper presents a comparison of remote sensors used by animals with those developed by humans. Remote sensor designers can learn to improve their sensor designs by studying animal sensors within a biomimetic framework.

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Article
Publication date: 18 January 2021

Shahla U. Umar and Tarik A. Rashid

The purpose of this study is to provide the reader with a full study of the bat algorithm, including its limitations, the fields that the algorithm has been applied…

Abstract

Purpose

The purpose of this study is to provide the reader with a full study of the bat algorithm, including its limitations, the fields that the algorithm has been applied, versatile optimization problems in different domains and all the studies that assess its performance against other meta-heuristic algorithms.

Design/methodology/approach

Bat algorithm is given in-depth in terms of backgrounds, characteristics, limitations, it has also displayed the algorithms that hybridized with BA (K-Medoids, back-propagation neural network, harmony search algorithm, differential evaluation strategies, enhanced particle swarm optimization and Cuckoo search algorithm) and their theoretical results, as well as to the modifications that have been performed of the algorithm (modified bat algorithm, enhanced bat algorithm, bat algorithm with mutation (BAM), uninhabited combat aerial vehicle-BAM and non-linear optimization). It also provides a summary review that focuses on improved and new bat algorithm (directed artificial bat algorithm, complex-valued bat algorithm, principal component analyzes-BA, multiple strategies coupling bat algorithm and directional bat algorithm).

Findings

Shed light on the advantages and disadvantages of this algorithm through all the research studies that dealt with the algorithm in addition to the fields and applications it has addressed in the hope that it will help scientists understand and develop it.

Originality/value

As far as the research community knowledge, there is no comprehensive survey study conducted on this algorithm covering all its aspects.

Details

World Journal of Engineering, vol. 18 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

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Article
Publication date: 13 July 2012

Xin‐She Yang and Amir Hossein Gandomi

Nature‐inspired algorithms are among the most powerful algorithms for optimization. The purpose of this paper is to introduce a new nature‐inspired metaheuristic…

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Abstract

Purpose

Nature‐inspired algorithms are among the most powerful algorithms for optimization. The purpose of this paper is to introduce a new nature‐inspired metaheuristic optimization algorithm, called bat algorithm (BA), for solving engineering optimization tasks.

Design/methodology/approach

The proposed BA is based on the echolocation behavior of bats. After a detailed formulation and explanation of its implementation, BA is verified using eight nonlinear engineering optimization problems reported in the specialized literature.

Findings

BA has been carefully implemented and carried out optimization for eight well‐known optimization tasks; then a comparison has been made between the proposed algorithm and other existing algorithms.

Originality/value

The optimal solutions obtained by the proposed algorithm are better than the best solutions obtained by the existing methods. The unique search features used in BA are analyzed, and their implications for future research are also discussed in detail.

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Article
Publication date: 8 August 2016

Asma Chakri, Rabia Khelif and Mohamed Benouaret

The first order reliability method requires optimization algorithms to find the minimum distance from the origin to the limit state surface in the normal space. The…

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1126

Abstract

Purpose

The first order reliability method requires optimization algorithms to find the minimum distance from the origin to the limit state surface in the normal space. The purpose of this paper is to develop an improved version of the new metaheuristic algorithm inspired from echolocation behaviour of bats, namely, the bat algorithm (BA) dedicated to perform structural reliability analysis.

Design/methodology/approach

Modifications have been embedded to the standard BA to enhance its efficiency, robustness and reliability. In addition, a new adaptive penalty equation dedicated to solve the problem of the determination of the reliability index and a proposition on the limit state formulation are presented.

Findings

The comparisons between the improved bat algorithm (iBA) presented in this paper and other standard algorithms on benchmark functions show that the iBA is highly efficient, and the application to structural reliability problems such as the reliability analysis of overhead crane girder proves that results obtained with iBA are highly reliable.

Originality/value

A new iBA and an adaptive penalty equation for handling equality constraint are developed to determine the reliability index. In addition, the low computing time and the ease implementation of this method present great advantages from the engineering viewpoint.

Details

Multidiscipline Modeling in Materials and Structures, vol. 12 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

Open Access
Article
Publication date: 11 April 2018

Mohamed A. Tawhid and Kevin B. Dsouza

In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed…

Abstract

In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed algorithm is called Hybrid Binary Bat Enhanced Particle Swarm Optimization Algorithm (HBBEPSO). In the proposed HBBEPSO algorithm, we combine the bat algorithm with its capacity for echolocation helping explore the feature space and enhanced version of the particle swarm optimization with its ability to converge to the best global solution in the search space. In order to investigate the general performance of the proposed HBBEPSO algorithm, the proposed algorithm is compared with the original optimizers and other optimizers that have been used for feature selection in the past. A set of assessment indicators are used to evaluate and compare the different optimizers over 20 standard data sets obtained from the UCI repository. Results prove the ability of the proposed HBBEPSO algorithm to search the feature space for optimal feature combinations.

Details

Applied Computing and Informatics, vol. 16 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

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Article
Publication date: 19 June 2019

Wensheng Xiao, Qi Liu, Linchuan Zhang, Kang Li and Lei Wu

Bat algorithm (BA) is a global optimization method, but has a worse performance on engineering optimization problems. The purpose of this study is to propose a novel…

Abstract

Purpose

Bat algorithm (BA) is a global optimization method, but has a worse performance on engineering optimization problems. The purpose of this study is to propose a novel chaotic bat algorithm based on catfish effect (CE-CBA), which can effectively deal with optimization problems in real-world applications.

Design/methodology/approach

Incorporating chaos strategy and catfish effect, the proposed algorithm can not only enhance the ability for local search but also improve the ability to escape from local optima traps. On the one hand, the performance of CE-CBA has been evaluated by a set of numerical experiment based on classical benchmark functions. On the other hand, five benchmark engineering design problems have been also used to test CE-CBA.

Findings

The statistical results of the numerical experiment show the significant improvement of CE-CBA compared with the standard algorithms and improved bat algorithms. Moreover, the feasibility and effectiveness of CE-CBA in solving engineering optimization problems are demonstrated.

Originality/value

This paper proposed a novel BA with two improvement strategies including chaos strategy and catfish effect for the first time. Meanwhile, the proposed algorithm can be used to solve many real-world engineering optimization problems with several decision variables and constraints.

Details

Engineering Computations, vol. 36 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 30 July 2019

Shi Yin and Ming Zhu

This paper aims to quantify the dependence relationship of bat algorithm’s (BA) behaviour on the factors that could possibly affect the outputs, and rank the importance of…

Abstract

Purpose

This paper aims to quantify the dependence relationship of bat algorithm’s (BA) behaviour on the factors that could possibly affect the outputs, and rank the importance of the various uncertain factors thus suggesting research priorities.

Design/methodology/approach

This paper conducts a sensitivity analysis based on variance decomposition of factors in both of original and improved BA. The data sets for sensitivity analysis are generated by optimal Latin hyper sampling in the design of experiment. The optimal factor sets are screened by stochastic error bar measures for the effective and robust implementation of BA.

Findings

The paper reveals the inner dependent relationship between factors and output in both of original and improved BA. It figures out the weakness in original BA and improves that. It suggests that uncertainty brought about by factors are mainly caused by the interaction effect and all the higher-order term in sensitivity indices for both of original and improved BA. It ranks the main effect and the total effect of factors and screens out some optimal factor sets for BA.

Originality/value

This paper quantifies the dependence relationship of BA’s behaviour on the factors that could affect outputs using sensitivity analysis based on variance decomposition.

Details

Engineering Computations, vol. 36 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 16 May 2019

Bourahla Kheireddine, Belli Zoubida and Hacib Tarik

This study aims to improve the bat algorithm (BA) performance for solving optimization problems in electrical engineering.

Abstract

Purpose

This study aims to improve the bat algorithm (BA) performance for solving optimization problems in electrical engineering.

Design/methodology/approach

For this task, two strategies were investigated. The first one is based on including the crossover technique into classical BA, in the same manner as in the genetic algorithm method. Therefore, the newly generated version of BA is called the crossover–bat algorithm (C-BA). In the second strategy, a hybridization of the BA with the Nelder–Mead (NM) simplex method was performed; it gives the NM-BA algorithm.

Findings

First, the proposed strategies were applied to solve a set of two standard benchmark problems; then, they were applied to solve the TEAM workshop problem 25, where an electromagnetic field was computed by use of the 2D non-linear finite element method. Both optimization algorithms and finite element computation tool were implemented under MATLAB.

Originality/value

The two proposed optimization strategies, C-BA and NM-BA, have allowed good improvements of classical BA, generally known for its poor solution quality and slow convergence rate.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 3 June 2019

Bourahla Kheireddine, Belli Zoubida and Hacib Tarik

This paper aims to deal with the development of a newly improved version of teaching learning based optimization (TLBO) algorithm.

Abstract

Purpose

This paper aims to deal with the development of a newly improved version of teaching learning based optimization (TLBO) algorithm.

Design/methodology/approach

Random local search part was added to the classic optimization process with TLBO. The new version is called TLBO algorithm with random local search (TLBO-RLS).

Findings

At first step and to validate the effectiveness of the new proposed version of the TLBO algorithm, it was applied to a set of two standard benchmark problems. After, it was used jointly with two-dimensional non-linear finite element method to solve the TEAM workshop problem 25, where the results were compared with those resulting from classical TLBO, bat algorithm, hybrid TLBO, Nelder–Mead simplex method and other referenced work.

Originality value

New TLBO-RLS proposed algorithm contains a part of random local search, which allows good exploitation of the solution space. Therefore, TLBO-RLS provides better solution quality than classic TLBO.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 1 February 2021

R. Srilakshmi and Jayabhaskar Muthukuru

The mischievous nodes that defy the standard corrupt the exhibition of good nodes considerably. Therefore, an intrusion discovery mechanism should be included to the…

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Abstract

Purpose

The mischievous nodes that defy the standard corrupt the exhibition of good nodes considerably. Therefore, an intrusion discovery mechanism should be included to the mobile ad-hoc network (MANET). In this paper, worm-hole and other destructive malignant attacks are propelled in MANET.

Design/methodology/approach

A wireless ad-hoc network also called as mobile ad-hoc network (MANET) is a gathering of hubs that utilizes a wireless channel to exchange information and coordinate together to establish information exchange among any pair of hubs, without any centralized structure. The security issue is a major difficulty while employing MANETs.

Findings

Consequently, the attacks due to the malicious node activity are detected using Hybrid Reactive Search and Bat (HRSB) mechanism to prevent the mischievous nodes from entering the network beneath the untruthful information. Moreover, the attack detection rate and node energy are predicted for determining the lifetime of the node.

Originality/value

The simulation outcomes of the proposed HRSB technique are evaluated with the prevailing methods. The comparison studies have proven the efficacy of the current research model by attaining high attack detection rate and achieving more network lifetime.

Details

International Journal of Intelligent Unmanned Systems, vol. 10 no. 1
Type: Research Article
ISSN: 2049-6427

Keywords

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