Multi-Objective Intercity Carpooling Route Optimization Considering Carbon Emission

In recent years, intercity carpooling has been vigorously developed in China. Considering the differences between and intracity carpooling, this paper first defines path optimization problem with time window. Based on balance of interests among passengers, platform, government, a multi-objective function is constructed to minimize passenger cost, maximize platform revenue, carbon emission vehicle capacity, boarding alighting points, service, other constraints. Secondly, order further improve coordination ability search speed operator, uses particle swarm algorithm help operator remember previous position iterative information, designs PSO (Particle Swarm Optimization) improved NSGA-II (Non-dominated Sorting Genetic Algorithm) solve model. Finally, feasibility model verified by numerical analysis Xi’an–Xianyang carpool. The results show that 1 5-8-O-D-16-13, 2 7-3-6-O-D-15-11-14, 3 2-1-4-O-D-12-10-9. Compared algorithm, PSO-NSGA-II designed significant advantages global convergence speed.