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N. C. Sahoo
Researcher at Universiti Teknologi Petronas
Publications - 52
Citations - 1416
N. C. Sahoo is an academic researcher from Universiti Teknologi Petronas. The author has contributed to research in topics: Particle swarm optimization & Switched reluctance motor. The author has an hindex of 18, co-authored 46 publications receiving 1276 citations. Previous affiliations of N. C. Sahoo include Multimedia University & Indian Institutes of Technology.
Papers
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Solving shortest path problem using particle swarm optimization
TL;DR: A modified priority-based encoding incorporating a heuristic operator for reducing the possibility of loop-formation in the path construction process is proposed for particle representation in PSO, which surpasses those of recently reported genetic algorithm based approaches for this problem.
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A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems
N. C. Sahoo,Krishna Prasad +1 more
TL;DR: It is observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration, and the fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution.
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Optimal reconfiguration of radial distribution systems using a fuzzy mutated genetic algorithm
TL;DR: A new method based on a fuzzy mutated genetic algorithm for optimal reconfiguration of radial distribution systems (RDS) is presented, which overcomes the combinatorial nature of the reconfigurations problem and deals with noncontinuous multi-objective optimization.
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Multi-objective particle swarm optimization based on fuzzy-Pareto-dominance for possibilistic planning of electrical distribution systems incorporating distributed generation
TL;DR: A multi-objective planning approach for electrical distribution systems under uncertainty in load demand incorporating distributed generation (DG) and the advantages of networks obtained using the proposed planning approach in the context of DG integration are described.
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Multi-objective planning of electrical distribution systems using dynamic programming
TL;DR: In this article, a dynamic programming based planning algorithm for optimization of the feeder routes and branch conductor sizes is proposed, and a set of Pareto solutions is obtained using a weighted aggregation of the two objectives with different weight settings.