A Comprehensive Review of the Pigeon-Inspired Optimization Algorithm

Abstract

Optimization is the essence of most of the decisions one has to make, whether it is some complex engineering design or just be a simple holiday planning. Fundamentally, most of the optimization problems are solved using traditional methods of numerical computing. However, while addressing complex engineering problems, these methods exhibit some short falls as they are sensitive to initial values and fail to attain consistency in global solutions. In contrast, researchers proposed contemporary algorithms mostly on the basis of ‘learning’ strategies. Most of these algorithms are nature-inspired algorithms. Swarm Intelligence is one very predominant nature inspired optimization technique based on social organisms such as bacteria, bees, ants, fireflies, pigeons etc., for finding solutions to optimization problems. This paper mainly focuses on reviewing a newly developed bio-inspired optimization approach, namely, Pigeon Inspired Optimization (PIO) algorithm. Pigeons are simple and intelligent birds, which can travel long distances in search of food and return home without getting lost. This act inspired researchers and led to the interpretation that pigeons navigate using Earth’s magnetic field, differences in altitude of sun and by remembering few landmarks. The success of any algorithm is assured when the algorithm is able to explore and exploit globally in the problem domain. Probing PIO on various applications helps us to understand the algorithm better.