Research On Joint Optimization Of Order Allocation And Distribution For E-commerce Under Data-driven Model

The increasing popularity of hardware facilities such as mobile clients and network platforms has led to an increase in the number and methods of information acquisition,thus it is a great challenge for e-business to utilize data resources to optimize enterprise service.The explosive growth of data drives the improvement of data transfer ef-ficiency and the frequency of information exchange,so it is feasible to optimize the order alloca-tion and distribution jointly for e-commerce under data-driven model.In recent years,research on order allocation and logistics distribution problem has made a lot of research results,but has not realized from the perspective of data driven joint optimization.In fact,with the development of network platform technology,the compactness,real-time capability and interactivity of order allocation and distribution services become more obvious,for example,it is increased for the relevance between consumer data dimen-sions and operational systems,which contain warehouses,vehicles,and transportation of distribution processes.Such performance parameters can be fed back timely to the deci-sion-making center.According to Taguchi Optimization Theory,service quality is the basic premise to meet consumer demand,service ability is the basic guarantee of service execution effect,and sustainability is a strategic management optimization goal,and then the whole optimization process is a progressive process of gradually.Therefore,taking service quality,service ability and service sustainability as foothold,it is neces-sary to carry out the decision-making of the joint optimization of order allocation and distribution for e-commerce under data-driven model with important theoretical signifi-cance and practical significance.This dissertation researches on the theories and methods about the joint optimiza-tion of order allocation and distribution for e-commerce under data-driven model,and mainly carries out the following research work:Firstly,the relevant concepts and theoretical analysis on joint optimization of order allocation and distribution for e-commerce under data-driven model are given.The the-oretical framework is designed based on the progressive three elements of Taguchi Op-timization in chronological order,and the theories and methods of data-driven joint op-timization decision-making problem are enriched and developed.To begin with,com-bining with preference theory,optimizing e-commerce of order allocation and distribu-tion quality from the perspective of consumers is supposed to the basic premise of joint optimization;then analyzing the theory of bullwhip effect,service capabilities of e-commerce order allocation and distribution is regarded as the basic guarantee of joint optimization;last discussing sustainable optimization theory is perceived as the goal of the joint optimization of e-commerce order allocation and distribution.At the same time,it provides a general theoretical framework for the study of related problems and pro-vides theoretical guidance for the analysis and description of research problems.Secondly,according to the joint optimization for e-commerce order allocation and delivery service quality,three stages of research are carried out.Above all,the complete classification of the quality of service preferences for the recipients includes memoryless,memorability,uncertainty,and the whole.Furthermore,based on the four types of re-ceivers,the mathematical joint optimization model is constructed for e-commerce order allocation and distribution service quality with different preferences.Eventually,the complexity derivation of four types of planning solution space is given,and the dynamic programming algorithm is designed for the memoryless recipients when the cost is a linear function,and the approximate algorithm for three other types of receiving party.Compared with traditional batch planning,the design of data-driven approach made up for the inadequacy of the research on personalized quality demand solution,and the re-search conclusion has reference value for guiding management practice.Thirdly,there are three aspects of the studies on data-driven joint optimization of order allocation and distribution capability.On the one hand,relevant features are se-lected from training data samples to ensure that the error cost of data information classi-fication is minimized within the joint decision-making process,thereby reducing the bullwhip effect;on the other hand,considering that consumers may influence the e-commerce decision-making during the cooling-off period allowed,the issue of self-construction or outsourcing for e-commerce delivery service capability is given with three different degrees from the perspective of cooperation;besides,according to the three-stage dynamic game order,the sub-game equilibrium solutions under three differ-ent conditions are inversely deduced,and the optimal solution set of self-built and out-sourced delivery service capabilities is obtained under the online purchasing environ-ment.The game model with the joint data of the order cancel and logistics distribution will compensate for the defect of service flexibility and the lack of ability to cope with uncertainty disturbance,and reduce the economic cost of e-commerce enterprise and product suppliers.Fourthly,aiming at the joint optimization problem of e-commerce order allocation and distribution sustainability,the resource sharing strategies are proposed from the three goals of economy,environment and society.From the economic perspective,a cost optimization model for the distribution resource sharing strategy is constructed based on the rationality of matching resources for sharing order information,warehouse infor-mation,transportation information,vehicle information,distribution service capabilities,and service time windows.From the environmental perspective,based on the data en-velopment analysis method,a variety of emission reduction factors are designed to evaluate the carbon emission performance and allocation indicators for order allocation and distribution resource sharing strategies.From the social perspective,the revenue sharing strategy is designed to determine a reasonable revenue sharing coefficient,and stable cooperation between the exclusive distribution resource service provider and the e-commerce platform is realized.The research shows that sustainable optimization not only ensure economic benefits but also environmental benefits and social benefits.The data-driven research on the joint optimization of order allocation and distribu-tion for e-commerce has enriched and developed the relevant theories of optimization,providing guidance for further study on more complex data-driven joint optimization theories and methods.Meanwhile,the research can not only realize the joint optimiza-tion of the e-commerce order allocation and distribution system,but also provide appro-priate decisions for the optimization of service quality,service capability,and service sustainability of e-commerce companies,and is of great significance for the effective use of data resources.