Distribution System Network Reconfiguration by using Artificial Bee Colony Algorithm.

Kumar, Dharani Hemanth; Babu, P. Suresh; Lalitha, M. Padma

doi:10.9790/1676-09114852

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…train neural networks [32], medical pattern classification [33] and clustering problems [34], solving TSP [35], leaf-constrained minimum spanning tree [36], network reconfiguration problem in a radial distribution system [37] 8.…”

Section: New Velocitymentioning

confidence: 99%

Nature-Inspired Algorithms: State-of-Art, Problems and Prospects

Agarwal¹,

Mehta²

2014

IJCA

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Nature-inspired algorithms have gained immense popularity in recent years to tackle hard real world (NP hard and NP complete) problems and solve complex optimization functions whose actual solution doesn't exist. The paper presents a comprehensive review of 12 nature inspired algorithms. This study provides the researchers with a single platform to analyze the conventional and contemporary nature inspired algorithms in terms of required input parameters, their key evolutionary strategies and application areas. A list of automated toolboxes available for directly evaluating these nature inspired algorithms over numerical optimization problems indicates the need for unified toolbox for all nature inspired algorithms. It also elucidates the users with the minimum and maximum dimensions over which these algorithms have already been evaluated on benchmark test functions. Hence this study would aid the research community to know what all algorithms could be examined for large scale global optimization to overcome the problem of 'curse of dimensionality'.

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Section: New Velocitymentioning

confidence: 99%