PATU DIGUA, QUASI-OPPOSITIONAL BASED TEACHER ACTIONS IN THE SOCIETY AND QUANTUM MONASTERY CHIEF SELECTION INSPIRED OPTIMIZATION ALGORITHMS

Abstract

Patu digua search (BKS) optimization algorithm, Quasi-Oppositional based Teacher Actions in the Society - inspired Optimization (SGS) Algorithm, Quantum Monastery chief selection Inspired Optimization (QRMCSO) Algorithm are designed and applied to solve the Electrical loss reduction problem. Patu digua search optimization algorithm is designed based on the stalking deeds of Patu digua. The stalking approaches are deliberated by oppression, examination, and hurdling on the prey. Lévy flights are engaged as an ancillary of persistent irrational engagements to emulate the fudging performance. Chaotic sequences are integrated in Patu digua search optimization algorithm. In Quasi-Oppositional based Teacher Actions in the Society - inspired Optimization Algorithm, exploration region is envisaged as a synchronize organization with a quantity of axes equivalent to the decision parameters. Quasi-Opposition approach integrated into the approach to enhance the search and quality of the solution. In QRMCSO, before picking a successor Head of the monastery will do various analyses and these standards are imitated in the design through Chebyshev serviceable connexion system.