A HYBRID GENETIC ALGORITHM FOR PARTITIONING OF DATA MODEL IN DISTRIBUTION MANAGEMENT SYSTEMS

Darko Capko, Aleksandar Erdeljan, Srdjan Vukmirovic, Imre Lendak

Abstract


In this paper, we propose a Hybrid Genetic Algorithm for data model partitioning of power distributionnetwork. Analytical functions are the core of Distribution Management Systems (DMSs). Efficient calculation of thefunctions is of the utmost importance for the DMS users; the necessary preconditions for the efficient calculation areoptimal load balancing of processors and data model partitioning among processors. The proposed algorithm is appliedto different real models of power distribution systems. It obtains better results than classical evolutionary algorithms(Genetic Algorithm and Particle Swarm Optimization). The Hybrid Genetic Algorithm also achieves better results thanmultilevel algorithm (METIS) in cases of small graphs.

http://dx.doi.org/10.5755/j01.itc.40.4.981


Keywords


graph partitioning; genetic algorithm; Distributed Management System; Common Information Model

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