Chaotic predator–prey biogeography-based optimization approach for UCAV path planning

This paper proposes a novel Chaotic Predator–Prey Biogeography-Based Optimization (CPPBBO) approach for solving the path planning problems of Uninhabited Combat Air Vehicle (UCAV). To generate optimal or near-optimal flight path, path planning is a key part of UCAV assignment planning system. The planned path can ensure UCAV avoid hostile threats and safely reach an intended target with minimum fuel cost. An improved biogeography-based optimization algorithm is presented for solving the optimization problem in the path planning process. Biogeography-Based Optimization (BBO) is a new bio-inspired optimization algorithm. This algorithm searches for global optimum mainly through two steps: migration and mutation. To enhance the global convergence of the BBO algorithm, the chaos theory and the concept of predator–prey are adopted to get new search mechanism. The comparative simulation results are given to show that our proposed CPPBBO algorithm is more efficient than basic BBO, CBBO and PPBBO in solving the UCAV path planning problems.