Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms

In recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization problem depends upon the efficacy of these two...

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Main Authors: Akash Saxena, Shalini Shekhawat, Rajesh Kumar
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Modelling and Simulation in Engineering
Online Access:http://dx.doi.org/10.1155/2018/4945157
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author Akash Saxena
Shalini Shekhawat
Rajesh Kumar
author_facet Akash Saxena
Shalini Shekhawat
Rajesh Kumar
author_sort Akash Saxena
collection DOAJ
description In recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization problem depends upon the efficacy of these two phases. These two phases are tied with a bridging mechanism, which plays an important role. This paper presents an application of chaotic maps to improve the bridging mechanism of Grasshopper Optimisation Algorithm (GOA) by embedding 10 different maps. This experiment evolves 10 different chaotic variants of GOA, and they are named as Enhanced Chaotic Grasshopper Optimization Algorithms (ECGOAs). The performance of these variants is tested over ten shifted and biased unimodal and multimodal benchmark functions. Further, the applications of these variants have been evaluated on three-bar truss design problem and frequency-modulated sound synthesis parameter estimation problem. Results reveal that the chaotic mechanism enhances the performance of GOA. Further, the results of the Wilcoxon rank sum test also establish the efficacy of the proposed variants.
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institution Kabale University
issn 1687-5591
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publishDate 2018-01-01
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spelling doaj-art-76eb2fc0a3f3413fb85b48742f40301d2025-02-03T06:44:35ZengWileyModelling and Simulation in Engineering1687-55911687-56052018-01-01201810.1155/2018/49451574945157Application and Development of Enhanced Chaotic Grasshopper Optimization AlgorithmsAkash Saxena0Shalini Shekhawat1Rajesh Kumar2Swami Keshvanand Institute of Technology, Jaipur 302017, IndiaSwami Keshvanand Institute of Technology, Jaipur 302017, IndiaMalaviya National Institute of Technology, Jaipur 302017, IndiaIn recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization problem depends upon the efficacy of these two phases. These two phases are tied with a bridging mechanism, which plays an important role. This paper presents an application of chaotic maps to improve the bridging mechanism of Grasshopper Optimisation Algorithm (GOA) by embedding 10 different maps. This experiment evolves 10 different chaotic variants of GOA, and they are named as Enhanced Chaotic Grasshopper Optimization Algorithms (ECGOAs). The performance of these variants is tested over ten shifted and biased unimodal and multimodal benchmark functions. Further, the applications of these variants have been evaluated on three-bar truss design problem and frequency-modulated sound synthesis parameter estimation problem. Results reveal that the chaotic mechanism enhances the performance of GOA. Further, the results of the Wilcoxon rank sum test also establish the efficacy of the proposed variants.http://dx.doi.org/10.1155/2018/4945157
spellingShingle Akash Saxena
Shalini Shekhawat
Rajesh Kumar
Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
Modelling and Simulation in Engineering
title Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
title_full Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
title_fullStr Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
title_full_unstemmed Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
title_short Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms
title_sort application and development of enhanced chaotic grasshopper optimization algorithms
url http://dx.doi.org/10.1155/2018/4945157
work_keys_str_mv AT akashsaxena applicationanddevelopmentofenhancedchaoticgrasshopperoptimizationalgorithms
AT shalinishekhawat applicationanddevelopmentofenhancedchaoticgrasshopperoptimizationalgorithms
AT rajeshkumar applicationanddevelopmentofenhancedchaoticgrasshopperoptimizationalgorithms