Optimal Stochastic Package Delivery Planning with Deadline: A Cardinality Minimization in Routing
February 28, 2018 Β· Declared Dead Β· π IEEE Vehicular Technology Conference
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Authors
Suttinee Sawadsitang, Siwei Jiang, Dusit Niyato, Ping Wang
arXiv ID
1803.02232
Category
cs.AI: Artificial Intelligence
Cross-listed
math.OC
Citations
4
Venue
IEEE Vehicular Technology Conference
Last Checked
4 months ago
Abstract
Vehicle Routing Problem with Private fleet and common Carrier (VRPPC) has been proposed to help a supplier manage package delivery services from a single depot to multiple customers. Most of the existing VRPPC works consider deterministic parameters which may not be practical and uncertainty has to be taken into account. In this paper, we propose the Optimal Stochastic Delivery Planning with Deadline (ODPD) to help a supplier plan and optimize the package delivery. The aim of ODPD is to service all customers within a given deadline while considering the randomness in customer demands and traveling time. We formulate the ODPD as a stochastic integer programming, and use the cardinality minimization approach for calculating the deadline violation probability. To accelerate computation, the L-shaped decomposition method is adopted. We conduct extensive performance evaluation based on real customer locations and traveling time from Google Map.
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