An asymptotically optimal algorithm for pickup and delivery problems
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Frazzoli_An asymptotically optimal.pdf
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Author(s)
Pavone, Marco
Frazzoli, Emilio
Treleaven, Kyle Ballantyne
Date Issued
December 2011
Journal
Proceedings of the IEEE Conference on Decision and Control and European Control
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Treleaven, Kyle, Marco Pavone, and Emilio Frazzoli. “An asymptotically optimal algorithm for pickup and delivery problems.” In IEEE Conference on Decision and Control and European Control Conference, 584-590. Institute of Electrical and Electronics Engineers, 2011.
Version
Author's final manuscript
Abstract
Pickup and delivery problems (PDPs), in which objects or people have to be transported between specific locations, are among the most common combinatorial problems in real-world operations. One particular PDP is the Stacker Crane problem (SCP), where each commodity/customer is associated with a pickup location and a delivery location, and the objective is to find a minimum-length tour visiting all locations with the constraint that each pickup location and its associated delivery location are visited in consecutive order. The SCP is a route optimization problem behind several transportation systems, e.g., Transportation-On-Demand (TOD) systems. The SCP is NP-Hard and the best know approximation algorithm only provides a 9/5 approximation ratio. We present an algorithm for the stochastic SCP which: (i) is asymptotically optimal, i.e., it produces a solution approaching the optimal one as the number of pickups/deliveries goes to infinity; and (ii) has computational complexity O(n[superscript 2+ϵ]), where n is the number of pickup/delivery pairs and ϵ is an arbitrarily small positive constant. Our results leverage a novel connection between the Euclidean Bipartite Matching Problem and the theory of random permutations.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/CDC.2011.6161406
