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.
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Riva Sanseverino, E., Di Silvestre, M.L., Gallea, R. (2013). Pareto-optimal Glowworm Swarms Optimization for Smart Grids Management. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_3
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DOI: https://doi.org/10.1007/978-3-642-37192-9_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37191-2
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