面向众包平台的合单即时配送优化及激励机制研究

The development of crowdsourcing platforms has facilitated the matching of the idle vehicle and the transport demand of large-scale scattered goods, which has attracted great attentions from both the academic and the industries of e-commerce and logistics. However, it is inefficiency and unable to satisfy customers’ heterogeneous request for the response time, which is resulted from the adopting mode of grabbing orders independently. Therefore, this research will study the order consolidation optimization problem of real-time delivery and the incentive mechanism for the customers’ heterogeneous request. Considering the dynamic information of the demand orders and the delivery vehicle on the crowdsoucing platform, the methodology of online algorithm and competitive analysis will be adopted. Firstly, the principle of order consolidation of real-time delivery will be revealed by analyzing the characteristic of crowdsourced delivery. Secondly, the order consolidation real-time delivery optimization problem will be solved by establishing an order allocation and routing model, designing some online algorithms and analyzing their performances. Thirdly, some incentive functions for the customers’ heterogeneous request will be introduced into the crowdsouced delivery problem. The order consolidation real-time delivery models with a fixed punishment and a linear punishment will be established, respectively. An incentive mechanism of delivery service under variety circumstances will be designed by solving the models and studying the results. Finally, some numerical simulation will be conducted to validate and improve the theoretical models and the algorithms. The results of this study will enrich the research field of the crowdsourced delivery, which also can be used to promote the function of the existing logistics crowdsourcing platforms.

众包平台由于其能够快速匹配大规模分散物流需求与自由运力而受到了电商与物流业界的高度关注，亦成为学界研究的焦点。但现阶段的独立抢单模式配送效率低，无法满足客户不同的响应要求，是众包物流领域亟待解决的关键问题。因此，本项目聚焦众包平台的合单即时配送优化及激励机制研究。首先，通过分析众包配送特征，揭示众包平台的合单配送机理；其次，运用在线理论与竞争分析的方法建立合单即时配送订单分配与路径优化理论模型，设计双边动态的合单配送在线算法，分析算法性能，解决众包平台的合单即时配送优化难题；再次，引入客户异质化响应的激励函数，分别建立固定额度和线性函数惩罚的合单即时配送优化模型，通过模型求解与结果探究，设计多情景的配送服务激励机制；最后，通过数值仿真研究验证和完善理论模型与算法。研究成果对阐明众包平台合单配送机制具有重要意义，可为众包物流理论研究提供新的思路，在众包配送平台功能升级方面具有重要的应用前景。

众包配送是将共享经济理念引入物流领域的新型配送模式。众包配送平台赖以生存的关键在于通过即时配送需求订单与共享运力的快速匹配，提升客户响应速度，降低商家配送成本，为配送员谋取收益。然而，现阶段众包平台的独立抢单模式导致配送效率低，无法满足客户不同的响应要求。因此，面向众包平台的合单即时配送优化策略设计，考虑客户异质化响应的激励机制的研究是众包配送领域亟待解决的关键问题。鉴于此，本项目围绕合单配送机制、订单分配与路径优化、激励机制等方面，运用在线理论、启发式算法设计与仿真研究等方法对面向众包平台的合单即时配送优化问题展开了一系列的研究。. 主要研究内容和重要进展包括：（1）单取货点的合单即时配送优化模型与算法研究。其中分别研究了以完成所有订单的时间之和最小、总服务时间最小、配送距离最短为目标的单配送员和多配送员的实时取送货在线车辆路径优化问题。主要运用在线理论与竞争分析方法研究了不同情境下的问题下界，并设计了相应的在线策略，进行了策略的竞争比分析与证明，得到了不同情境下所适用的策略。（2）任意取货点的合单即时配送优化模型与算法研究。主要运用算法设计与仿真分析的方法分别研究了基于众包平台的外卖实时配送订单分配与路径优化问题和跑腿代购即时配送优化问题，通过大量的数值仿真实验得到了不同算法的适用性和敏感性。（3）客户异质化响应的合单即时配送优化问题及其激励机制研究。分别建立固定额度、线性、发红包、打赏四种激励机制下的订单分配与路径优化模型，并设计了四种订单分配与路径规划策略。通过大量模拟仿真实验验证模型的合理性并对比研究不同激励机制的适用场景。（4）拓展研究了电动汽车、无人驾驶技术、实时路况监测等新型技术在末端配送中的优化问题。. 研究成果将完善和提升众包配送平台的功能和效率，将提高物流服务质量，提升客户响应速度，减少车辆的无效行使，助力城市的可持续发展。