Research On The Fourth Party Logistics Route Optimization Under The Uncertain Environment With Complex Timetable Limitations

The concept of Fourth Party Logistics(4PL)was first proposed by Accenture.In1998,Accenture mentioned in the book "Strategic Supply Chain Coordination" : The fourth-party logistics model is a supply chain integrator whose core is the selection of supply chain integration,third party logistics(3PL)suppliers and information industry providers Manage and mobilize resource allocation to provide customers with comprehensive service supply chain solutions.However,due to the immature information technology and weak hardware equipment,the fourth party logistics model has not been promoted and used;now with the maturity and implementation of intelligent and information technology,4PL has once again become a hot spot in the logistics industry and academia topic.This paper summarizes the relevant literatures of 4PLRP at home and abroad,starting from the 4PLRP problem considering the fixed timetable limit in the uncertain environment and the 4PLRP problem under the complex timetable limit.According to the hierarchy from easy to difficult,the complex time under the uncertain environment is studied.The fourth party logistics path optimization problem restricted by the table,the research content of the paper is as follows:Study the 4PLRP that considers fixed schedule constraints in uncertain environments.Considering the constraints of fixed schedules and the constraints of multiple supply points and one demand point,a 4PLRP interval optimization model was constructed,and a genetic algorithm with variable length coding was designed to solve the case based on the NP difficulty of the model.The results show that the constructed NP-difficult model and the designed algorithm can quickly select the transportation scheme with the best cost according to the requirements of the decision maker,and also provide basis support for decision-making.At the same time,the sensitivity analysis of genetic algorithm crossover and mutation probability found that:when the crossover probability is 0.8 and the mutation probability is 0.2,the genetic algorithm solves the problem more efficiently.Study the 4PLRP that considers the constraints of complex schedules in uncertain environments.On the basis of the fixed schedule,the transportation delay time is used to replace the transportation time,and the variable length theory is introduced to visually characterize the 4PL transportation delay time,comprehensively considering the characteristics of complex schedule restrictions and multi-commodity flow transportation restrictions Build a "4PL service provider-consignor" dual-constrained NP hard model,and design a bee colony algorithm to solve the case.The research results show that the double-constrained model can effectively meet the requirements of 4PL service providers and shippers,and provide suitable transportation solutions for both.At the same time,through the sensitivity analysis of the robust control parameters,it is found that the effect is the best when the control parameter is 0.3;at this point,there are new departure shifts in the sections,8 ?33?33 ?40 ?14 ?33,and the number of new additions is 1.Taking 0.3 as the boundary,with the decrease of the control parameters,the response iteration number of the optimal value of the transportation cost gradually shifts from 33 generations to 62 generations;with the increase of the control parameter,the response overlap number of the optimal value gradually increases Large,and there is a tendency to exceed the limit set by the algorithm.In addition,comparing the solution efficiency of the bee colony algorithm and the genetic algorithm for this case,it was found that the genetic algorithm faced a complex 4PL network topology,the graph structure showed a stepwise convergence,and the descent gradient was large,the gradient surface was wide,and the final iteration was 50 times Convergence;the bee colony algorithm iterates the descending slope of the graph smoothly,the trend presents a linear function slope,and the slope of the graph increases as the robust control parameter approaches 0.3.It can be seen that compared with genetic algorithms,bee colony algorithm is more efficient in solving complex problems.This article starts from the actual operation of 4PL and pays attention to the practical problems of the uncertainty of the transportation environment faced by 4PLRP and the fact that the railway transportation model has the characteristics of dispatch schedules;it studies the fourth-party logistics path of complex dispatch schedules under uncertain environments Excellent is of certain theoretical significance and practical application value.