Incomplete Information Game and Simulation of Logistics Supervision

Abstract

This article aims to improve incomplete information game of logistics supervision and its practice feasibility. For the uncertainty of logistics enterprises’ type, firstly we established an incomplete information game of logistics supervision. Second we carried on Harsanyi transformation to convert it into a complete but imperfect information game. Meanwhile we use Trigonometric distribution to solve uncertainty of logistics enterprises’ type. By investigation, the most likely value is 0.77 in Trigonometric distribution. Lastly, Monte Carlo (MC) simulation is adopted to simulate players’ behavior strategy and expected benefit. The expected benefits of logistics demand enterprises and 3PLs are 33.5667 and 16.5375 respectively. The simulation results show that the randomizing coincides with the probability distribution of the Mix Nash equilibrium above 98.7%.