Optimization Design of RSU for Internet of Vehicles Based on Decomposition Multi-Objective Evolutionary Algorithm

With the development of economy and society, the layout of China's Internet of Vehicles industry has been continuously improved. RSUs play an important role in the Internet of Vehicles. But it faces problems such as high cost, low coverage, low signal quality, and high energy efficiency. The RSU coverage problem in the Internet of Vehicles is a multi-objective optimization problem. An improved decomposition-based MOEA (MOEA/D), called MOEA/D-ODE, is proposed, which employs the OBL method to produce an opposite population and a new differential evolution (DE) operator during the evolving process. The OBL method could enhance the probability of obtaining a better candidate population, and the DE operator helps the population to move closer to the Pareto optimal solutions, so that the convergence of the algorithm to the Pareto front could be accelerated effectively. So we propose this algorithm to solve the multi-objective optimization problem of vehicle networking RSU.