Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
A solution of the bicriteria vehicle scheduling problems with time and area-dependent travel speeds
Computers and Industrial Engineering
Time-Varying Travel Times in Vehicle Routing
Transportation Science
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
Optimizing goods assignment and the vehicle routing problem with time-dependent travel speeds
Computers and Industrial Engineering
A variable neighborhood search for the multi-depot vehicle routing problem with loading cost
Expert Systems with Applications: An International Journal
A hybrid meta-heuristic for multi-objective vehicle routing problems with time windows
Computers and Industrial Engineering
Survey of Green Vehicle Routing Problem: Past and future trends
Expert Systems with Applications: An International Journal
A variable-reduction technique for the fixed-route vehicle-refueling problem
Computers and Industrial Engineering
Green vehicle routing in urban zones - A neuro-fuzzy approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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The vehicle routing problem (VRP) has been addressed in many research papers. Only a few of them take time-dependent travel speeds into consideration. Moreover, most research related to the VRP aims to minimize total travel time or travel distance. In recent years, reducing carbon emissions has become an important issue. Therefore, fuel consumption is also an important index in the VRP. In this research a model is proposed for calculating total fuel consumption for the time-dependent vehicle routing problem (TDVRP) where speed and travel times are assumed to depend on the time of travel when planning vehicle routing. In the model, the fuel consumption not only takes loading weight into consideration but also satisfies the ''non-passing'' property, which is ignored in most TDVRP-related research papers. Then a simulated annealing (SA) algorithm is proposed for finding the vehicle routing with the lowest total fuel consumption. An experimental evaluation of the proposed method is performed. The results show that the proposed method provides a 24.61% improvement in fuel consumption over the method based on minimizing transportation time and a 22.69% improvement over the method based on minimizing transportation distances.