Research On The Optimization Storage Slotting And Order Picking With Non-traditional Warehouse

Storage efficiency optimization is an important way to improve the overall benefit of the supply chain and promote the value-added of the supply chain.With the goal of optimizing warehousing operations and improving operational efficiency,this paper focuses on three aspects in warehousing operations,including layout design,storage slotting and order picking.Considering the current situation of insufficient theoretical research and low operational efficiency,the paper focuses on the related research on non-traditional warehousing location allocation and picking optimization.Firstly,according to the literature review at home and abroad,this paper introduces several major optimization problems in warehousing operation and corresponding solutions.Extend the non-traditional layout design concept and research status;The optimization research is put forward from two aspects of location allocation and picking operation.Then,taking practical engineering problems as the background,the paper analyzes the characteristics of non-traditional layout warehousing(Fishbone type)and the optimization problem of storage slotting,and constructs an optimization model of storage slotting with the goal of warehouse entry efficiency and shelf stability.A multiobjective normalization method based on Delphi and AHP is proposed.The adaptive genetic algorithm(AGA)and improved particle swarm optimization(MPSO)were designed.In AGA,dynamic adaptive strategy was adopted to improve selection,crossover and mutation operators to overcome early "precocity" and improve local search at the end stage.In MPSO,nonlinear variable inertia weight and time-varying acceleration learning factor are introduced to improve the early global search ability and the late convergence slowness.The detailed design and implementation process of the two improved algorithms are given.Furthermore,the characteristics of the optimization problem of non-traditional layout are summarized.The similarities and differences with TSP and the complexity of traditional layout are analyzed.The shortest path model of any two picking points under Fishbone layout is given.Taking the shortest picking operation time as the optimization objective,the picking operation optimization models were constructed under the two conditions of picking equipment with and unlimited load constraints.The improved genetic algorithm(IGA),the improved ant colony algorithm(IACA)and the improved simulated annealing algorithm(ISA)are designed.On the basis of introducing the specific improvement strategy,the detailed design ideas and implementation steps of each algorithm are given.Finally,on the basis of the actual case data,MATLAB is used to program and solve the algorithms,verifying the accuracy of the model and the effectiveness of the algorithm.The applicability and superiority of the improved algorithm are verified by comparing with the traditional method and the standard algorithm.The improved algorithms proposed in this paper can provide feasible solutions for the diversity requirements in practical engineering applications.