Pareto-optimal glowworm swarms optimization for smart grids management

Authors:
Eleonora Riva Sanseverino;Maria Luisa Di Silvestre;Roberto Gallea
Affiliations:
DIEETCAM, Universita' di Palermo, Palermo, Italy;DIEETCAM, Universita' di Palermo, Palermo, Italy;DICGIM, Universita' di Palermo, Palermo, Italy
Venue:
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Year:
2013

Citing 3
Cited 0

Multicriteria Optimization

Multicriteria Optimization
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

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Abstract

This paper presents a novel nature-inspired multi-objective optimization algorithm. The method extends the glowworm swarm particles optimization algorithm with algorithmical enhancements which allow to identify optimal pareto front in the objectives space. In addition, the system allows to specify constraining functions which are needed in practical applications. The framework has been applied to the power dispatch problem of distribution systems including Distributed Energy Resources (DER). Results for the test cases are reported and discussed elucidating both numerical and complexity analysis.