Medical Wastes Logistics System Analysis Based On Game Theory And ABM

The management of medical wastes logistics is of great social concern.However,related research hardly reflects characteristics of the complex social system.This paper studies the evolution of medical wastes system based on game theory and ABM.To enhance the learning ability of agents,the application of Q-learning in ABM is determined.Evolutionary Game Theory(EGT)is used to analyze incomplete rationality groups.In order to combine Q learning,EGT and ABM,a new multi-agent system model framework based on the traditional one including environment,Q-learning single-agent module and group agents module based on EGT and Q-learning Dynamic is designed.Interactions are designed through instantaneous rewards.The realization of Beijing medical wastes logistics system using the new framework is then present.Main attributes,behaviors and rewards of hospitals,companies,disposal plants,government and NGOs are designed respectively,the group evolutionary mechanism of hospitals as well.Experiments on how the system evolved from the current status and after improvement are designed.The results show how each agent behave during the process,how the system acts correspondingly and point out the improvement as well.The results can be a solid guidance to the improvement of the actual system.The new framework proposed is effective for the study of complex system problems.