基于即时物流的饿了么外卖物流配送模式选择研究

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基于即时物流的饿了么外卖物流配送模式选择研究-知知文库网
基于即时物流的饿了么外卖物流配送模式选择研究
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Research on the choice of delivery mode of elemetakeout delivery based on real-time logistics[Abstract]With the rapid development of the society,people pay more attentionto the timeliness and convenience,and the logistics industry has made rapid progress."instant logistics"has emerged as The Times require.At present,takeout logistics isstill the key task of instant logistics.Takeout logistics has a high requirement ontimeliness and relies on good delivery services to improve user experience.Therefore,eleme takeout chooses to build its own logistics distribution system--hummingbirddistribution,so as to improve the delivery service level.However,the self-builtdistribution system also brings the problem of high distribution cost.In recent years,the concept of crowdsourcing has emerged in the field of logistics.In the field oftake-out delivery,a relatively low-cost crowdsourcing distribution model has beenapplied,thus forming a development situation in which self-run distribution andcrowdsourcing distribution modes coexist.As a leader in the industry,eleme takeout not only needs to provide high-leveldelivery services,but also needs to take into account the delivery cost.Only whenboth are considered,can the company operate smoothly.Self-run delivery andcrowdsourced delivery have their own advantages and disadvantages.Eleme needs toanalyze and calculate the appropriate proportion of self-run delivery andcrowdsourced delivery to maximize the benefits of the take-out platform.Based on eleme Delivery as the research object,first described by elemeTake-out distribution present situation and the existing problems,and analyzes itsproblems,through the establishment of which help to delivery service levels anddistribution cost as the objective function,with proprietary delivery order proportionand distribution effect for the multi-objective optimization model of decisionvariables,through the MATLAB calculation analysis and the changes of targetvariables and decision variables finalized hungry take-away optimal proportion of
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