Optimal Selecting and Sequencing of Cargo Flight Scheme Based on Uncertainty Multi-Attribute Decision-Making

Air Cargo plays an important role in integrated logistics system. A scientific and rational cargo flight planning is a prerequisite for successful implementation of air cargo transportation. The selection of cargo flights is a multi-attributes decision making process. It is difficult for decision-makers to give a definite value and evaluation indicator for every factor involved. In this paper, the author comprehensively analyzes the influence factors of flight planning and builds an optimal evaluation index system. Furthermore, based on the evaluation of each index in the form of interval number, the evaluating model for optimization of air cargo planning is established by applying relative membership degree rule. Finally, an example is given to show the effectiveness and feasibility of this method. Air Cargo plays an important role in the comprehensive logistics system, and a scientific and rational cargo flight scheme (CFS) is the prerequisite for the successful implementation of air cargo. The purpose of developing CFS is to optimize aircrafts, routes, personnel, capital and other limited resources of airlines so that decision makers can determine the scientific and reasonable routes, aircraft and flight schedule which can achieve maximum efficiency and cost-effectiveness. There are a lot of factors for decision makers to consider in the process of developing the CFS, and these factors have their own different attributes and different significances respectively, as the result, the evaluation of these factors is difficult to quantify. The CFS will determine whether air cargo meets the freight demand, and has directly influenced company's survival and growth. Much research has been conducted on optimal selection of passenger flight scheme, however, very few of the research focuses on optimal selection of cargo flight scheme (Sun, et al. 2004), (Feng, et al. 2009).Therefore, the study on selecting and sequencing of CFS has important and practical significance. In this paper, the authors establish CFS evaluation index system. Due to the co-existence of qualitative and quantitative attributes where quantitative attributes are difficult to accurately quantify and the attribute weights are difficult to determine, to solve this problem, this paper uses the uncertain multi-attribute decision model where the attribute values and the weights are interval numbers