EDA++: Estimation of Distribution Algorithms With Feasibility Conserving Mechanisms for Constrained Continuous Optimization-Reference-Cited by-同舟云学术

EDA++: Estimation of Distribution Algorithms With Feasibility Conserving Mechanisms for Constrained Continuous Optimization

Published:2022-10 Issue:5 Volume:26 Page:1144-1156
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Shirazi Abolfazl¹^ORCID,Ceberio Josu²^ORCID,Lozano Jose A.¹^ORCID

Affiliation:

1. Machine Learning Group, Basque Center for Applied Mathematics, Bilbao, Spain

2. Intelligent Systems Group and the Computer Science and Artificial Intelligence Department, University of the Basque Country, Donostia-San Sebastian, Spain

Funder

Secretara de Estado de Investigacin Desarrollo e Innovacin

la Caixa Foundation

Eusko Jaurlaritza

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/9906461/09721397.pdf?arnumber=9721397

Reference23 articles.

1. A square lattice probability model for optimising the Graph Partitioning Problem

2. Distance-based exponential probability models on constrained combinatorial optimization problems

3. Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art

4. A Survey of Outlier Detection Methodologies

5. Boundary Search for Constrained Numerical Optimization Problems in ACO Algorithms

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