Abstract
Autonomous delivery robots (ADRs) as green last-mile delivery alternatives to traditional vans have received much attention due to the rapid development of Physical Internet (PI). However, their low efficiency limits the application in the last-mile delivery because few orders per trip are delivered. Also, the cost and emission impact of new motilities on the PI-enabled last-mile delivery network is still not clear. To address these issues, this study developed an innovative two-echelon delivery system that combines traditional vans and ADRs to take their advantages for the last-mile delivery. The objective of this study was to minimize transportation costs and emissions through solving an extension of a two-echelon vehicle routing problem considering load-dependent unit transport costs and unit emissions with mixed vehicles and multiple depots. The problem was formulated as a mixed-integer programming model and then efficiently solved by a cluster-based artificial immune algorithm, in which an improved clustering method was employed to assign the customers. The experimental results showed that the proposed solution approach efficiently solved the problem with better solutions than existing approaches in the relevant literature. Several managerial implications on configuring the two-echelon delivery system were also provided for potential applications.
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