Abstract
The returning of homing pigeons to their lofts from remote and unfamiliar locations with great accuracy remains a mystery. Pigeon-inspired optimization (PIO), which is a novel mono-objective continuous optimization algorithm, is inspired by the hidden mechanism behind the remarkable navigation capacity of homing pigeons. Since their development, PIO and its variants have been widely applied to various fields ranging from combinatorial optimization to multi-objective optimization in many areas, such as aerospace, medicine, and energy. This study aims to review the modifications of PIO from four aspects of improvement measures, namely, component replacement, operation addition, structure adjustment, and application expansion. It also summarizes the problems of existing research and plots the course of future effort.
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