Abstract
This paper investigates the capacitated green vehicle routing problem (GVRP) with time-varying vehicle speed and soft time windows. The GVRP is developed as a multi-objective mixed integer nonlinear programming (MINLP) model that incorporates a fuel consumption calculation algorithm. The proposed model considers the vehicle load and capacity as well as time-varying speed in order to account for traffic congestion. An improved non-dominated sorting genetic algorithm (NSGA-II) with adaptive strategies and greedy strategies is developed to solve the GVRP. The results of numerical experiments show that the consumption of fuel in a supply chain can be decreased sharply without any significant loss in customer satisfaction. The proposed NSGA-II has a better capability and efficiency than the original NSGA-II. Our experiments also indicate that the proposed model outperforms most of the best-known solutions obtained from the traditional modeling approaches.
Original language | English |
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Article number | 106011 |
Journal | Computers and Industrial Engineering |
Volume | 137 |
DOIs | |
Publication status | Published - Nov 2019 |
Keywords
- Capacitated vehicle routing problem
- Fuel consumption
- Green logistics
- Time-varying speed
- Traveling salesman problem