Operations Dept. Seminar

Dynamic Type Matching


We consider an intermediary's problem of dynamically matching demand and supply of heterogeneous types in a periodic-review fashion.  More specifically, there are two disjoint sets of demand and supply types.  There is a reward associated with each possible matching of a demand type and a supply type.  In each period, demand and supply of various types arrive in random quantities.  The platform's problem is to decide on the optimal matching policy to maximize the total discounted rewards minus costs, given that unmatched demand and supply will incur waiting or holding costs, and will be carried over to the next period with abandonments.  For this dynamic matching problem, we provide sufficient conditions (which we call modified Monge conditions) only on matching rewards such that the optimal matching policy follows a priority hierarchy among possible matching pairs: if some pair of demand and supply types is not matched as much as possible, all pairs that have strictly lower priority down the hierarchy should not be matched.  This result is obtained by a generalization of the classic augmenting path approach and adapt it to the stochastic problem, which can be viewed as a generalized, stochastic and dynamic, assignment/transportation problem.  This paper is co-authored with Yun Zhou, Rotman School of Management, University of Toronto.

Fee: [Yes/No/Varies]

Contact Information:
Tedda Nathan
Dept. Administrator, Dept. of Operations

Friday, April 15, 2016 from 10:30 a.m. to noon
Peter B. Lewis Building, room 118
11119 Bellflower Road
Cleveland, OH 44106-7235
United States
Speaker(s): Prof. Ming Hu
Hu, Ming paper


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