Positive point charge potential field based ACO algorithm for multi-objective evacuation routing optimization problem

Multi-objective evacuation routing optimization problem is defined to find out optimal evacuation routes for a group of evacuees according to multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a positive-point-charge-potential-field-like model (PPCPF-like model), and we proposed PPCPF-ACO algorithm to solve this problem based on the proposed model. In PPCPF-ACO algorithm, we use non-dominated sorting based roulette wheel routing method (NSRWR) to further improve evacuation efficiency. In Wuhan Sports Center case, we compared PPCPF-ACO with HMERP-ACO (hierarchical multi-objective evacuation routing problem - ant colony optimization) and traditional ACO according to three evacuation objectives, namely, total evacuation time, total evacuation route length and cumulative congestion degree. The experimental results show that PPCPF-ACO has a better performance than HMERP-ACO algorithm and traditional ACO algorithm while solving multi-objective evacuation routing optimization problem.