A Combinatorial Assessment Method for the Sequencing Problem and its Application in Waterway Traffic Environments

A combinatorial assessment method (CAM) model is presented to better assess and solve sequencing problems with respect to safety issues in waterway traffic environments. The CAM model proposed involves four parts: the attributive matching model (AMM) and its algorithm, the multi-method calculation, the information filtering model (IFM), and the information fusion algorithm (IFA). Among them, the AMM and its algorithm for the matching level can initially select suitable methods. The multi-method calculation can apply the chosen methods and unify the dimensions of all solutions. The IFM, based on the iterative cluster analysis, can remove errors and interferences through several iterations to improve the solution. The IFA, based on the mean value method, the Borda count rule, and the Copeland method, can examine the convergence of the solutions and provide a high quality one. Another noticeable function is that a customized model for a particular object might be obtainable based on the proposed CAM model. In the second part of the paper, the CAM model is used to solve a channel sequencing problem with respect to the safety levels of a navigable environment of the Yangtze River. A customized CAM-CSP model is formed, whose generality is tested subsequently through a similar but more complicated channel sequencing problem. The solution indicates that the proposed CAM model can enhance the assessment’s quality and help to provide a customized model to solve similar problems conveniently.