Research On Distributed Multi Agent Optimization Method For Port Job Scheduling Problem

In the traditional ant colony optimization research,the accuracy of the algorithm isstudied deeply,and the speed of the algorithm and the ability to deal with large scale problems are ignored.At the same time,in the actual business,port operation scheduling is also faced with similar needs,in the event of an emergency,often plan to keep up with the changes,the need to quickly find a new optimal solution in a complex environment.In this paper,a distributed multi-Agent ant colony algorithm is proposed to solve the large-scale optimization problem,and it is applied to the real-time scheduling problem of port operation.To achieve this goal,firstly,on the basis of traditional ant colony algorithm,the improved state transition rules,the combination of local search algorithm,the improved ant colony algorithm can avoid low quality solutions,to improve the speed of convergence.After that,this paper improves the algorithm of ant colony algorithm,separates the computing part from the control part,and makes it adapt to the distributed structure.A distributed ant colony algorithm is constructed by combining it with distributed multi-Agent system.In order to verify the reliability of the algorithm,this paper implements the distributed ant colony algorithm and the system on the JADE platform,and compares the results with the results of previous studies on the international standard VRPTW.The results show that the distributed ant colony algorithm performs well in solving the accuracy,speed,reliability and ability to solve large-scale problems.Finally,according to the port operation scheduling problem,taking into account the work effect may occur in the process of the operation of unexpected factors,using the ant colony algorithm and distributed system,simulation and optimization of port operation scheduling.The experimental results show that the proposed algorithm can meet the requirements of real-time scheduling,and the feasibility of the proposed distributed ant colony algorithm and the system is verified.In this paper,through theoretical and practical experiment proves the efficiency of distributed ant colony algorithm,and the feasibility of using distributed multi Agent system and real-time algorithm to solve the problem,I hope through this research leads to more study on distributed multi-Agent optimization,solving more simulated optimization problems can be faster and better.