Low-Carbon Vehicle Routing Models and Optimization Algorithms with Hybrid Time Window.

The large amounts of greenhouse gases generated in the logistics and transportation industry worsen global climate deterioration, jeopardizing the human living environment. A multi-objective nonlinear planning model for vehicle routing problems (VRPs) was established by considering VRPs with carbon emission constraints to realize the shortest vehicle mileage and the minimum carbon emission. An improved simulated annealing algorithm was proposed to solve the model. The farthest insertion heuristic method, combined with a relocation operator, was applied in the reinsertion operation to determine the preferred insertion back to the customer point and the optimal insertion point. The customer point with the largest minimum target increment was removed from the removed customer points and inserted into the optimal insertion point until all of them were inserted. Results demonstrate that the proposed algorithm outperforms the common genetic algorithms and forbidden search algorithms in similar studies with strong global optimization search capability. The improved algorithm could solve low-carbon VRP with high sensitivity and effectiveness. [ABSTRACT FROM AUTHOR]