Abstract
Frequent time window changing disruptions result in high secondary delivery rates in the last mile delivery. With the rapid growth of parcel volumes in online shopping, the time window changing disruptions could translate to substantial delivery cost-wastes. In recent years, customer pickup (CP), a new delivery mode that allows customers to pick up their parcels from shared delivery facilities, has provided a new way to deal with such disruptions. This study proposed a disruption recovery problem with time windows change in the last mile delivery in which customers can be served through home delivery (HD) or CP. A variant variable neighborhood descent (VVND) algorithm was presented to solve the problem. Computational experiments based on a set of instances were tested, and results were compared with other heuristics in the literature, which have affirmed the competitiveness of the model and algorithm.
Highlights
IntroductionAccording to the State Post Bureau of China, the parcel volume of online shopping of 3.67 billion in 2011 increased to 40.06 billion in 2017, with an average growth rate of more than 48% within six years
The rapid e-commerce growth results in a fast increase of parcel delivery
This study proposed a disruption recovery problem with time windows change in the last mile delivery in which customers can be served through home delivery (HD) or customer pickup (CP)
Summary
According to the State Post Bureau of China, the parcel volume of online shopping of 3.67 billion in 2011 increased to 40.06 billion in 2017, with an average growth rate of more than 48% within six years. This increase of parcel volume caused the increase of the one-time delivery failure rate. Reducing the high delivery failure rate to deal with the frequent time window changing disruptions had become a key issue in the last mile delivery of online shopping. This study proposed a DRP with time windows change in the last mile delivery to solve the practical problems and bridge the gap in the literature.
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