Two-modified emperor penguins colony optimization algorithms

Abstract

Meta heuristic algorithms are very important methods, they used mainly in solving combinatorial optimization problems. They are stochastic in manner and simulate the behavior of any population of particles. Meta heuristics algorithms try to find optimal or near to optimal solution when solving complex optimization problem. In this paper two modified emperor penguins colony optimization algorithms MEPC1 and MEPC2 were developed. Original Emperor Penguins Colony (EPC) algorithm simulates the behavior of emperor of penguins, two modifications are done to the original EPC, Archimedes and hyperbolic spiral like movement are used instead of logarithmic spiral like movement. The two modified algorithms are compared with the original algorithm through ten test functions; the results show that themodified algorithms are achieved better than the original one.