Real power loss reduction by enriched great frigatebird, grey forecast and constellation exploration optimization algorithms

In this paper Enriched Great frigatebird optimization (EGFO) algorithm, Grey forecast algorithm (GFA) and Constellation exploration optimization (CEO) algorithm are applied to solve the power loss decreasing problem. Basically Enriched Great frigatebird optimization (EGFO) algorithm is designed based on the immigration activity and bout action to acquire food from other birds. In EGFO algorithm Canis lupaster algorithm stalking activity and Virus infection algorithms, Robust, Feeble mode (to improve both exploration and exploitation) are integrated. Grey forecast algorithm (GFA) is a modest optimization algorithm with resilient examination ability. Reproduction procedure will create a function that estimates the law (exponential) for predicting the provisional population in descendant’s population through consecutive generations of the population sequence as a time sequence. Constellation exploration optimization (CEO) algorithm is stimulated by faunae examining behaviour in actual natural life. The constellation exploration optimization (CEO) algorithm is executed by means of a set of contender representatives (population) which is entitled as the constellation, and every representative is entitled as an associate. Proposed EGFO, GFA and CEO algorithms are validated in G01–G24 benchmark functions and IEEE test systems.