dc.description.abstract | The vehicle routing problem has been and remains a rich topic for researchers and practitioners. In the real world, however, there exist many uncertain or constantly varying factors, which affect the operation of vehicle routing plan and result in the higher cost or failure. These factors may include occurrence of customer, quantity of demand, travel time, deterioration of commodities, etc.
This thesis explores the extensional issues of vehicle routing problem with time windows in three parts. In the first part, the demand of customers and travel times may vary unexpectedly and a real-time, on-line operational vehicle dispatching and guiding system is established, taking the latest information of demand and traffic condition into account. The predictable travel time pattern is also considered as a time-dependent function in this model.
In the second part, the travel time is considered as a random variable and the optimal routes are found in the pre-trip planning. The researches considering the stochasticity of travel time are relatively rare in the past. In this part a stochastic programming model is established, and the objective is proved to have a lower bound. An optimal solution can be found by raising the lower bound. In addition, the stochasticity of the arrival time at a customer will not be affected by the accumulative stochasticity of all previous link travel time in this model.
The third part consists of integration of production scheduling and distribution for perishable goods. The perishable goods deteriorate as soon as they were produced and keep decaying when being delivered, resulting in deduction of revenue. The vehicle route as well as its delivery time and the production time should be considered in the phase of production scheduling, in order to reduce the deterioration and increase the profit. | en_US |