Myxomycete Navigation Optimization Algorithm And Application Of Manufacturing Enterprise Logistics

The optimal design of the logistics system is of great significance for reducing the production costs and improving the production efficiency of manufacturing enterprises.The complexity of modern enterprise logistics causes most companies to consider artificial intelligence algorithms,heuristic algorithms,and intelligent bionic algorithms when addressing logistics system design issues.As the latest hot spot in the field of intelligent bionics,the path navigation optimization ability of Myxomycetes is gradually being applied to the optimal design of logistics routes.The designed path network has good performance in terms of cost,efficiency,and fault tolerance.Based on the smart behavior of Myxomycetes,this paper attempts to propose a new intelligent bionic algorithm,which provides a new solution for modeling and simulation of manufacturing logistics system.The main research work of this dissertation is as follows:(1)According to the developmental features of Myxomycetes and the requirements for its growth,the culture environment is established to cultivate the protoplasm of Myxomycetes.On the basis of referring to the foreign research team's Myxomycete path optimization experiment,a multi-food sources experiment is designed and carried out.Combined with the maze model experiment of the Japanese research team,a positive feedback mechanism for Myxomycetes navigation optimization is given.(2)Based on the positive feedback mechanism of Myxomycete navigation optimization,a navigation optimization algorithm is built.It is found that the convergence speed of the Myxomycete algorithm is faster by comparing the optimization results of a typical complex path optimization example with the genetic algorithm.Since the original Myxomycete algorithm has redundant iterative problem,heuristic rules are proposed in combination with the positive feedback mechanism,the non-shortest path elimination model is designed,and found that the improved Myxomycete algorithm performs better on the convergence results.(3)The workshop quadratic assignment problem model is constructed based on the Myxomycete navigation optimization algorithm.The multi-objective function covering minimum flow rate,maximum area utilization,and network cross-congestion correction parameters is designed;the constraints including boundary and spacing constraints is given;and the validity and practicality of the model and algorithm are verified by comparing the optimized workshop layout with the original one of J company.(4)Based on the Myxomycete navigation optimization algorithm,the multi-vehicle path optimization model is constructed which aims to solve the material handling problem in the manufacturing enterprise logistics system.The path planning problem of automated guided vehicle is taken as the research object,the shortest path length is regarded as the target and the key constraint is to avoid the conflict collisions.The AGV path planning example of J company is studied,and its original handling scheme is compared with the experimental simulation scheme of Myxomycete to verify the validity and practicality of the model and algorithm.The study shows that the Myxomycete navigation optimization algorithm can effectively solve the logistics system path optimization problem in manufacturing companies,but the algorithm still has some defects and deficiencies,future research work can continue to explore in terms of algorithm optimization.