Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem

Alexander S. Estes, Michael O. Ball (2020) Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem. INFORMS Journal on Computing 33(2):785-807.

54 Pages Posted: 10 Nov 2017 Last revised: 20 Oct 2021

See all articles by Alexander Estes

Alexander Estes

University of Maryland

Michael O. Ball

University of Maryland - Decision and Information Technologies Department

Date Written: September 6, 2019

Abstract

We consider a dynamic, stochastic extension to the transportation problem. For the deterministic problem, there are known necessary and sufficient conditions under which a greedy algorithm achieves the optimal solution. We define a distribution-free type of optimality and provide analogous necessary and sufficient conditions under which a greedy policy achieves this type of optimality in the dynamic, stochastic setting. These results are used to prove that a greedy algorithm is optimal when planning a type of air traffic management initiative. We also provide weaker conditions under which it is possible to strengthen an existing policy. These results can be applied to the problem of matching passengers with drivers in an on-demand taxi service. They specify conditions under which a passenger and driver should not be left unassigned.

Keywords: transportation problem, Monge property, greedy policy, distribution-free optimization, stochastic optimization, combinatorial optimization

JEL Classification: C61

Suggested Citation

Estes, Alexander and Ball, Michael O., Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem (September 6, 2019). Alexander S. Estes, Michael O. Ball (2020) Monge Properties, Optimal Greedy Policies, and Policy Improvement for the Dynamic Stochastic Transportation Problem. INFORMS Journal on Computing 33(2):785-807., Available at SSRN: https://ssrn.com/abstract=3067130 or http://dx.doi.org/10.2139/ssrn.3067130

Alexander Estes (Contact Author)

University of Maryland ( email )

College Park
College Park, MD 20742
United States

Michael O. Ball

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4313 Van Munching Hall
College Park, MD 20815
United States
301-405-2227 (Phone)
301-405-8655 (Fax)

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