Journal ArticleDOI
Meta-heuristic framework: Quantum inspired binary grey wolf optimizer for unit commitment problem☆
K Srikanth,Lokesh Kumar Panwar,Bijaya Ketan Panigrahi,Enrique Herrera-Viedma,Enrique Herrera-Viedma,Arun Kumar Sangaiah,Gai-Ge Wang +6 more
TLDR
A quantum inspired binary grey wolf optimizer (QI-BGWO) to solve unit commitment (UC) problem and establishes the significance of proposed approaches among existing binary and quantum computing based heuristic approaches.About:
This article is published in Computers & Electrical Engineering.The article was published on 2017-08-01. It has received 82 citations till now. The article focuses on the topics: Quantum computer & Heuristic (computer science).read more
Citations
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Journal ArticleDOI
A novel nature-inspired algorithm for optimization: Squirrel search algorithm
TL;DR: This optimizer imitates the dynamic foraging behaviour of southern flying squirrels and their efficient way of locomotion known as gliding and provides more accurate solutions with high convergence rate as compared to other existing optimizers.
Journal ArticleDOI
Improved Binary Grey Wolf Optimizer and Its application for feature selection
TL;DR: Through verifying the benchmark functions, the advanced binary GWO is superior to the original BGWO in the optimality, time consumption and convergence speed.
Journal ArticleDOI
An improved NSGA-III algorithm with adaptive mutation operator for Big Data optimization problems
TL;DR: This study introduces an adaptive mutation operator to enhance the performance of the standard NSGA-III algorithm and shows results that indicate that NS GA-III with UC and adaptive mutationoperator outperforms the other NSGA -III algorithms.
Journal ArticleDOI
A Survey of Learning-Based Intelligent Optimization Algorithms
TL;DR: A comprehensive survey of LIOAs is conducted in this paper, which includes statistical analysis about LIOA, classification of L IOA learning method, application of LioAs in complex optimization scenarios, and L IOAs in engineering applications.
Journal ArticleDOI
Monarch butterfly optimization: A comprehensive review
TL;DR: This review study serves as a solid reference for future studies in the arena of SI and in particular the MBO algorithm including its modifications, hybridizations, variants, and applications.
References
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Journal ArticleDOI
Grey Wolf Optimizer
TL;DR: The results of the classical engineering design problems and real application prove that the proposed GWO algorithm is applicable to challenging problems with unknown search spaces.
Journal ArticleDOI
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
Kuk-Hyun Han,Jong-Hwan Kim +1 more
TL;DR: The results show that QEA performs well, even with a small population, without premature convergence as compared to the conventional genetic algorithm, and a Q-gate is introduced as a variation operator to drive the individuals toward better solutions.
Journal ArticleDOI
A genetic algorithm solution to the unit commitment problem
TL;DR: This paper presents a genetic algorithm (GA) solution to the unit commitment problem using the varying quality function technique and adding problem specific operators, satisfactory solutions to theunit commitment problem were obtained.
Proceedings ArticleDOI
Quantum-inspired genetic algorithms
Ajit Narayanan,M. Moore +1 more
TL;DR: It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain.
Journal ArticleDOI
An evolutionary programming solution to the unit commitment problem
TL;DR: The practical implementation of this procedure yielded satisfactory results when the EP-based algorithm was tested on a reported UC problem previously addressed by some existing techniques such as Lagrange relaxation (LR), dynamic programming (DP), and genetic algorithms (GAs).