Novel Western Jackdaw search, antrostomus swarm and Indian ethnic vedic teaching: inspired optimization algorithms for real power loss diminishing and voltage consistency growth

Lenin Kanagasabai ()
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Lenin Kanagasabai: Prasad V.Potluri Siddhartha Institute of Technology

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 6, No 7, 2895-2919

Abstract: Abstract This paper proposes Western Jackdaw search optimization (WJSO) algorithm, Antrostomus swarm optimization (ASSO) algorithm and Indian ethnic vedic teaching—inspired optimization (IEVTO) algorithm to solve the loss shrinking problem. Important aims of the paper are Power reliability extension, power oddity minimization and loss lessening. Western Jackdaw search optimization (WJSO) algorithm is designed based on the classiness demeanor of Western Jackdaw. Western Jackdaw search optimization algorithm distributes twofold segments of augmentation and variance. In prime segment, the flying design is crammed to propel up the process’s convergence in the course of the widespread optimal rate. In calculation, enlarging the impediment component in a certain collection will deliberately expand the examination area. ASSO algorithm is enthused by erudition the activities of Antrostomus in the swarm. Activities are communal movements, joint communication, satirist development, flying, and observance deeds are smeared for untangling the glitches. IEVTO algorithm is modeled by the inspiration from Guru–Shishya education system which has been found in ancient India. The new-fangled Gurus will progress their peculiar spiritual ethos by education expeditions. Around there are dual substitutes to complete their education expeditions: the stage selection stratagems is based on the Levy or by normal distribution. Proposed WJSO algorithm, ASSO algorithm and IEVTO algorithms are validated in test systems.

Keywords: Optimization; Power; Transmission loss; Western Jackdaw; Antrostomus; Swarm; Indian ethnic vedic teaching (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-022-01758-3

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