Paper Info
Title
Quantum-Inspired Evolutionary Algorithm for Optimization Problems Approach.
Abstract
This paper proposes a novel type of quantum-inspired evolutionary algorithm (QiEA) for numerical optimization inspired by the multiple universes principle of quantum computing, which is based on the concept and principles of quantum computing, such as a quantum bit and superposition of states. Numerical optimization problems are an important field of research with several applications in several areas: industrial plant optimization, data mining and many others, and although being successfully used for solving several optimization problems, evolutionary algorithms still present issues that can reduce their performances when faced with task where the evaluation function is computationally intensive. In order to address those issues the QiEA represent the most recent advance in the field of evolutionary computation. This work present some application about combinatorial and numerical optimization problems.
Year
DOI
Venue
2011
10.3233/978-1-60750-972-1-139
Frontiers in Artificial Intelligence and Applications
Keywords
Field
DocType
Quantum computing,Quantum inspired,Evolutionary algorithms,Optimization problems
Evolutionary algorithm,Computer science,Meta-optimization,Evolutionary computation,Multi-swarm optimization,Artificial intelligence,Evolutionary programming,Imperialist competitive algorithm,Machine learning,Genetic algorithm,Metaheuristic
Conference
Volume
ISSN
Citations 
234
0922-6389
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Maurizio Fiasché1499.23
Francesco Carlo Morabito233954.83