Smart logistics: distributed control of green crowdsourced parcel services
研究了一个面向即时配送的集成决策框架，通过马尔可夫决策过程和动态算法优化配送请求与路线调度，实验表明可增收6.4%并降低2.5%的燃油和排放成本。
This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.