| With the development of global economy, shipping industry has been developing rapidly in last decades. In the meantime, competition within the industry has become more and more fierce. Under such circumstance, liner shipping companies begin to construct hub-spoke network whose pattern suits the tendency of large-scale better.Optimizing hub-spoke network can help cut costs and improve service level directly. Feeder service network, as an important part of hub-spoke network, supports the service among hub ports. So it is also important to optimize feeder service network. On this context, this thesis analyzes the optimization of feeder service network, considering time window constraints and demand uncertainty. It is an application of vehicle routing problem with time windows. It can be described as follows:ships depart from hub port and arrive at several feeding ports, each voyage ends at the hub port and it is requested that every customer is serviced just once by one vessel within specified time window. The objective of the optimization is to choose appropriate routes for the vessels so that the operator can meet all the demands with minimum total cost.This thesis considers the situation that liner containerships depart from a hub port to serve several feeding ports, discharging cargoes. All ships are required to meet the specific time window constraints. On the basis of capacity constraints and time windows, this thesis analyzes a part of hub-spoke network with the optimization objective of minimizing the total cost. The deterministic feeder service network optimization problem with time windows and its counterpart robust optimization model with uncertain demand are set up. The robust model uses scenarios to describe demand uncertainty and it is mainly used to deal with the complicated uncertainty that would influence the decision-making. The results show that the robust model can well handle the uncertainty of shipping demand. |
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