Abstract
This work discusses the solution of a Large-scale global optimization problem named Security Constrained Optimal Power Flow (SCOPF) using a method based on Cross Entropy (CE) and Evolutionary Particle Swarm Optimization (EPSO). The obtained solution is compared to the Entropy Enhanced Covariance Matrix Adaptation Evolution Strategy (EE-CMAES) and Shrinking Net Algorithm (SNA). Experiments show the approach reaches competitive results.
Original language | English |
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Title of host publication | GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion |
Publisher | Association for Computing Machinery, Inc |
Pages | 69-70 |
Number of pages | 2 |
ISBN (Electronic) | 9781450367486 |
DOIs | |
Publication status | Published - 13 Jul 2019 |
Externally published | Yes |
Event | 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic Duration: 13 Jul 2019 → 17 Jul 2019 |
Publication series
Name | GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion |
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Conference
Conference | 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 13/07/19 → 17/07/19 |
Bibliographical note
Publisher Copyright:© 2019 Copyright held by the owner/author(s).
Keywords
- CE+EPSO
- LSGO
- SCOPF