Optimization Study On Three-dimensional Bin Packing Problem With Multiple Types Of E Company

The trend of industry 4.0 has brought automation and intelligent production.In manufacturing industries,it has resulted in expanded scale of manufacturing enterprises,increase of the amount of goods and orders,and diversity of the types of goods.These have posed a lot of challenges to the distribution of logistics centers.In the traditional mode,in order to achieve efficient delivery,most companies pick up goods separately with multiple people and cars.Workers’ operation depends on their experience without prepackaged information.The leader of Industry 4.0,the E logistics center of electrical company SE,is still used in this picking model.In order to avoid the constraints of reloading or packing arrangement,workers will prefer to select larger boxes than actually needed,which will result in the low loading rate,which means the waste of packaging materials and subsequent moving cost.According to the context,this thesis takes three-dimensional bin packing problem with multiple types as the research object.Firstly it introduces the current research status of the three-dimensional packing problem,as well as the categories and solving methods;Secondly,it will take the actual process of order distribution in E company as a starting point to introduce the situation of order,goods,containers,etc.,and analyze the existing loading rate and cost to figure out the optimal state based on historical data.This also paves the way for the optimization results of the later model.The problem of three-dimensional bin packing problem with multiple types is based on the perspective of business operation,as a result,constraints are formulated by the optimization goal of minimum cost and the actual packing rules based on a series of heuristic algorithms.A linear programming based on spatial coordinate system is proposed to solve this problem.And then this thesis will design a three-stage genetic algorithm,a three-stage natural number encoding and a partially mapped crossover operator,to iteratively optimize the selection of the box and the placement of the cargo to solve the model.Finally the algorithm is implemented by Python.The comparison between the optimized cost based on solved model and actual situation is showed in the end.This thesis constructs a three-dimensional bin packing problem with multiple types model to solve the problems of companies in reality,which has certain practical significance.The results show that after the optimization of the packing method,the cost of the packing is reduced by 36%,the utilization rate of the container space is increased by 10%,the volume of the packing case is reduced by 25%,and the number of used boxes is reduced by 51%,which significantly improve packing problems.In addition,after the optimization,the packing method can also reduce costs and improve benefits in terms of other packaging materials,handling and transportation,while improving customer satisfaction and achieving environmental friendly.