An Effective Multi-objective Evolutionary Algorithm Based on Decomposition for A Robot Rescue Path Planning Problem

The paper addresses a post-disaster robot rescue path planning problem where a number of people are trapped and a robot is used to rescue them. The objective functions are to minimize the number of deaths and the number of serious injuries. At first, a path matrix between two trapped people is obtained by using an improved A* algorithm. And then, an improved multi-objective evolutionary algorithm is proposed to find rescue paths with Pareto optimal or near-optimal solutions. At last, the proposed algorithm is compared with other multi-objective algorithms. The experimental results demonstrate the proposed algorithm can effectively plan a shorter path to reduce the number of deaths and serious injuries after disasters.