Monarch Butterfly Optimization-assisted Optimal Path Determination Solution

Abstract

Nature Inspired Computer (NIC) seeks to build novel computing technologies by analyzing how nature might be inspired to tackle complex issues under varying environmental situations. This has resulted in novel research in disciplines such as neural networks, swarm intelligence, evolutionary computing, and artificial immune systems. NIC technology is employed in nearly every field of physics, biology, engineering, economics, and management. In this paper, motivated by the nature-inspired approaches, Monarch Butterfly Optimization (MBO), is employed in this study to change the chromosomal parameter. The nonlinear polynomial approach is used together with conditional path selection criteria to aid with the movement of subpopulations and the amplitude parameter. The Ackley function is developed using a mathematical model of dependent path selection, and the influence of the amplitude parameter is calculated with an adjusting ratio. The results show better performance among the conditional path selection criteria in route optimization selection.