Robust Optimization Model Research On Liner Fleet Deployment Under Demand Uncertainty

With the development of world trade, the container liner shipping market also shows a high-speed development trend, and scale of world liner fleet is becoming larger and larger. The arrival of the economic crisis in2008and increasing spread after the economic crisis, highlight the problem of shipping capacity excess, and the increasing competition in shipping industry have forced shipping companies to take measures of slowing down, suspending and so on. During the slump period of liner shipping market, the liner companies how to properly adjust business strategy is particularly important, and the optimization about allocation of the ship fleet is a very important business strategy to improve the competitiveness of enterprises and avoid the risk.Container liner shipping is susceptible to many uncertain factors, such as polity, economics, social and external environment, market demand, ship technical and economic performance and so on, however, among these factors, the demand of container transport is the most important. Demand uncertainty will have a huge impact on the fleet deployment, and considering the demand uncertainty can make decision-making about fleet deployment more scientific. This paper aims to make research on liner fleet deployment under demand uncertainty, applying robust optimization method to solve the optimization problem under uncertainty, provide a viable theory and method of fleet deployment decisions for shipping companies.Based on careful analysis of the research in and abroad, this paper first summarizes the uncertain optimization methods, and introduces the theory of fleet deployment. Combined with the fleet deployment features, a liner fleet deployment model under certain demand is established for container transportation, collects data of ship operation, and tests the model by empirical analysis. Secondly, explores a new method based on the liner fleet deployment model under certain demand, establishes a robust optimization model on liner fleet deployment under demand uncertainty, compares robust optimization results with certainty optimal solution. Lastly, the main findings and the limitation of this research are displayed, and makes some expectation of the study.