Novel constrained multi-objective biogeography-based optimization algorithm for robot path planning

A constrained multi-objective biogeography-based optimization algorithm (CMBOA) was proposed to solve robot path planning (RPP). For RPP, the length and smoothness of path were taken as the optimization objectives, and the distance from the obstacles was constraint. In CMBOA, a new migration operator with disturbance factor was designed and applied to the feasible population to generate many more non-dominated feasible individuals; meanwhile, some infeasible individuals nearby feasible region were recombined with the nearest feasible ones to approach the feasibility. Compared with classical multi-objective evolutionary algorithms, the current study indicates that CMBOA has better performance for RPP.