Journal ArticleDOI
Cohort intelligence algorithm for discrete and mixed variable engineering problems
Ishaan R. Kale,Anand J. Kulkarni +1 more
TLDR
The performance of an emerging socio inspired metaheuristic optimization technique referred to as Cohort Intelligence (CI) algorithm is evaluated on discrete and mixed variable nonlinear constrained optimization problems.Abstract:
In this study, the performance of an emerging socio inspired metaheuristic optimization technique referred to as Cohort Intelligence (CI) algorithm is evaluated on discrete and mixed variable nonlinear constrained optimization problems. The investigated problems are mainly adopted from discrete structural optimization and mixed variable mechanical engineering design domains. For handling the discrete solution variables, a round off integer sampling approach is proposed. Furthermore, in order to deal with the nonlinear constraints, a penalty function method is incorporated. The obtained results are promising and computationally more efficient when compared to the other existing optimization techniques including a Multi Random Start Local Search algorithm. The associated advantages and disadvantages of CI algorithm are also discussed evaluating the effect of its two parameters namely the number of candidates, and sampling space reduction factor.read more
Citations
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Journal ArticleDOI
Data science for engineering design: State of the art and future directions
TL;DR: In this article, the authors present a literature review at the intersection between ED and DS, identifying the tools, algorithms and data sources that show the most potential in contributing to ED, and identifying a set of challenges that future data scientists and designers should tackle, to maximize the potential of DS in supporting effective and efficient designs.
Journal ArticleDOI
Image Steganography Capacity Improvement Using Cohort Intelligence and Modified Multi-Random Start Local Search Methods
TL;DR: Two steganographic techniques which use JPEG compression on greyscale image to hide secret text and a quantization table of size $$16\times 16$$16×16 is practiced instead of a standard JPEG quantization tables to improve the capacity.
Journal ArticleDOI
Multi-cohort intelligence algorithm for solving advanced manufacturing process problems
TL;DR: The performance of the algorithm has been validated by comparing the results with other variations of CI algorithm and several contemporary algorithms such as firefly algorithm, genetic algorithm, simulated annealing and particle swarm optimization.
Journal ArticleDOI
Multi-Cohort Intelligence algorithm: an intra- and inter-group learning behaviour based socio-inspired optimisation methodology
TL;DR: The proposed Multi-CI outperformed these algorithms in terms of the solution quality including objective function value and computational cost, i.e. computational time and functional evaluations.
Journal ArticleDOI
Improved Cohort Intelligence—A high capacity, swift and secure approach on JPEG image steganography
TL;DR: Modified version of cohort intelligence (CI) algorithm, referred to as Improved Cohort Intelligence (CI), was considered as a cryptography technique and implemented to generate optimized cipher text to propose a reversible data hiding scheme.
References
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Journal ArticleDOI
An efficient constraint handling method for genetic algorithms
TL;DR: GA's population-based approach and ability to make pair-wise comparison in tournament selection operator are exploited to devise a penalty function approach that does not require any penalty parameter to guide the search towards the constrained optimum.
Journal ArticleDOI
A new structural optimization method based on the harmony search algorithm
Kang-Seok Lee,Zong Woo Geem +1 more
TL;DR: A new structural optimization method based on the harmony search (HS) meta-heuristic algorithm, which was conceptualized using the musical process of searching for a perfect state of harmony to demonstrate the effectiveness and robustness of the new method.
Journal ArticleDOI
Discrete Optimization of Structures Using Genetic Algorithms
S Rajeev,C S Krishnamoorthy +1 more
TL;DR: A penalty‐based transformation method depends on the degree of constraint violation, which is found to be wellsuited for a parallel search using genetic algorithms.
Journal ArticleDOI
Mixed variable structural optimization using Firefly Algorithm
TL;DR: A recently developed metaheuristic optimization algorithm, the Firefly Algorithm, which mimics the social behavior of fireflies based on their flashing characteristics is used for solving mixed continuous/discrete structural optimization problems.