An Improved Scheduling of Vehicle Routing in Smart Cities by Multiverse Optimization

One of the research problems is the vehicle routing problem (VRP) in smart cities for smooth movement of the vehicles and less traffic in the smart cities. The dynamic vehicle routing structure is a problem where a time frame is given for each vehicle to reach the destination, and this is classified as VRP with time windows. The Solomon's datasets are utilized for this vehicle routing problem with time windows (VRPTW). The goal is to calculate the least number of vehicles using two variants of multiverse optimizer. The two variants of multiverse optimizer are compared with the other techniques in terms of the travelled distances, the number of vehicles and the computational time are analyzed, and the effectiveness is calculated for all the proposed models for the VRPTW problem.