2022 Theses Doctoral
Essays on Discrete Optimization: Optimal Stopping and Popular Matchings
This thesis studies two discrete optimization problems: ordering problems in optimal stopping theory and popular matchings. The main goal of this thesis is to find the boundary between NP-hardness and tractability for these problems, and whenever possible, designs polynomial-time algorithms for the easy cases and approximation schemes or prophet inequalities for the hard cases. In the first part of the thesis, we study ordering problems in optimal stopping theory. In the optimal stopping problem, a player is presented with 𝓃 random variables 𝑋₁, . . . , 𝑋n, whose distributions are known to the player, but not their realizations. After observing the realization of 𝑋ᵢ, the player can choose to stop and earn reward 𝑋ᵢ, or reject 𝑋ᵢ and probe the next variable 𝑋ᵢ₊₁. If 𝑋ᵢ is rejected, it cannot be accepted in the future. The goal of the player is to maximize the expected reward at stopping time. If the order of observation is fixed, the player can find the optimal stopping criteria using a dynamic program. In this thesis, we investigate the variant in which the player is able to choose the order of observation. What is the best ordering and what benefits does ordering bring?
Chapter 2 introduces the optimal ordering problem in optimal stopping theory. We prove that the problem of finding an optimal ordering is NP-hard even in very restricted cases where the support of each distribution has support on at most three points. Next, we prove an FPTAS for the hardness case and provide a tractable algorithm and a prophet inequality for two-point distributions. Chapter 3 studies the optimal ordering problem when the player can choose 𝑘 > 1 rewards before stopping. We show that finding an optimal static ordering is NP-hard even for very simple two-point distributions. Next, we prove an FPTAS for the hardness case and give prophet inequalities under static and dynamic policies for two-point distributions.
In the second part of the thesis, we study popular matchings. Suppose we are given a bipartite graph with independent sets 𝑨 and 𝐵. Each vertex in 𝑨 has a ranked order of preferences on the vertices in 𝐵, and vice versa. A matching 𝑴 is popular if for any other matching 𝑴′, the number of vertices that prefer 𝑴 is at least as much as the number of vertices that prefer 𝑴′.
Chapter 4 studies popular matchings. In the first part, we provide a general reduction which, through minor adjustments, proves NP-Hardness for a variety of different questions, including that of finding a max-weight popular matching. In the second part, we restrict our attention to graphs of bounded treewidth and provide a tractable algorithm for finding a max-weight popular matching.
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More About This Work
- Academic Units
- Industrial Engineering and Operations Research
- Thesis Advisors
- Sethuraman, Jaychandran
- Agrawal, Shipra
- Ph.D., Columbia University
- Published Here
- January 19, 2022