Research On Robust Optimization Model Of Picking Resource Allocation In Outfitting Center Of Large Ocean-going Passenger Ship

The outfitting project is of great significance to the construction of large oceangoing passenger ships.The distribution of outfitting materials is the key link to ensure the timely supply of outfitting materials,and the picking of outfitting materials is an important part of the distribution operation.Reasonable allocation of picking resources and timely and accurate completion of picking of outfitting materials with the minimum total picking cost are of great significance to the construction progress and cost control of large ocean-going passenger ships.At present,there is little research on the allocation of outfitting materials picking operation resources of large ocean-going passenger ships.In the previous research on allocation of operation resources of distribution centers,various queuing models played an important role,but most of them used queuing models with fixed input rate and service rate,and only studied the number of people and equipment ratio,without considering the reality that the input rate and service rate will change with the system state in actual production,and also ignored the law of diminishing marginal returns,equipment ratio,equipment type and no-use.Therefore,fitting and analyzing the picking operation of outfitting materials of large ocean-going passenger ships by dynamic queuing model,and studying the resource allocation model of picking operation by combining with robust optimization theory,can provide reference and decision basis for the allocation of picking resources of outfitting materials in shipyards,help shipyards to reduce logistics costs and ensure the quality of logistics services in shipyards.Firstly,this thesis sorts out the research of outfitting logistics operation,queuing model and operation resource allocation in shipyards.Secondly,according to the modern shipbuilding mode,the characteristics of outfitting material logistics of large ocean-going passenger ships,the functions of outfitting assembly center,and the palletizing management of outfitting materials are combed.The process,present situation,existing problems and qualitative optimization strategies of outfitting material picking of large ocean-going passenger ships are analyzed.Thirdly,based on the dynamic queuing model,the outfitting material picking operation is analyzed.Considering the factors such as diminishing marginal returns,equipment types,equipment ratio,etc.,as well as the uncertainty of labor cost and operation efficiency requirements,two resource allocation models for outfitting material picking operation of large ocean-going passenger ships based on uncertainty are built by combining the stochastic programming expectation model and the scenario set-based robust optimization theory,and the corresponding solution algorithms are written by Python.Then,the basic parameters are obtained by analyzing the actual cases,which are substituted into the expected value model and the robust optimization model,respectively,to obtain their respective picking resource allocation schemes and the minimum total cost,and the comparative analysis and sensitivity analysis are made with the minimum total cost and allocation schemes under certain scenarios.Finally,the Sim Py library of Python is used to simulate the queuing system of picking jobs under the resource allocation of the robust model,and the simulation results are compared with the model solution results,and the simulation results and total cost of the original configuration scheme and the configuration scheme obtained by the robust model in the example are compared.It is found that the robust optimization model can better solve the uncertainty problem in this thesis,which is more reasonable than the expected value model,and its robustness increases with the increase of punishment.It is also proved that the robust model and its configuration scheme are effective and feasible.