Multi-Constrained Routing Based on Particle Swarm Optimization and Fireworks Algorithm

This paper sets up a mathematical model that satisfies the multiconstrained routing optimization problem. By adding a penalty, multiple constraints are mapped to a fitness that satisfies multiple constraints. Then, it uses a heuristic routing algorithm based on particle swarm optimization (PSO) to perform heuristic routing search. Introducing the fireworks algorithm (FWA) based on the PSO search algorithm, our algorithm searches the optimal solution more quickly. Besides, it reduces the defect of PSO falling into the local optimum. Simulation shows the algorithm can effectively solve the multiconstrained routing problem in large-scale networks. While searching for optimal solutions, the success rate of the algorithm is about 5.21% higher than that of the standard PSO algorithm. That is improved by using the ant colony algorithm. The PSO-ACO algorithm is about 2.57% higher than the problem. The average cost of the final search is about 4.36% higher than that of the standard PSO algorithm. It is about 1.34% higher than the PSO-ACO algorithm improved by the ant colony algorithm.