Track Fitting And Fuzzy Optimal Scheduling For Inland Vessels

Global warming is becoming more and more serious in recent years.the figures, which was announced by the International Energy Agency (IEA) in2012, showed that the global Carbon emissions increased6tons every year from2006to2010,carbon emissions reached a new high in2011. With the rapid economic development, it is a big problem to control carbon dioxide emissions for emerging countries. Inland river shipping has a lot of advantages, such as small investment, large capacity, low cost and so on; however, the ship as the emitter is facing a great pressure now, global greenhouse gas emissions has been paid much attention by people, and is a realistic problem for shipping industry to solve urgently.The paper introduces the concept of earth projection and the general expressions, focuses on Gauss Kruger projection of cylindrical transverse projection,use the theory formulas and the figures of projection to convert the ship’s latitude and longitude figures into the plane figures, then according to the characteristics of figures’distribution, research the steering movement of ship by the ship maneuvering motion equations, put forward an algorithm to solve the steering quality index K、T,calculate the new course distance of ship, and the turning steering process of ship approximates as that the ship is aroand a fixed points for a steady circular motion, find out the relation of steering angle velocity and curvature radius, It bases on Least squares piecewise cubic curve to fit the track and set up the model of ship.In the calculation of model, it convert to the equality constrained quadratic programming by the equality constrained least squares method, and the calculations of the model is achieved after that.finally, it bases on the fuzzy linear programming knowledge and the assumptions of the mode to establish the scheduling model;then according to the solving method of the fuzzy linear programming, it sets expansion parameters and the membership function, the model is transformed into the mixed linear programming model, and then base on the transformation to find out the solution, then use an example to explain.