Theses - Sloan School of Management
http://hdl.handle.net/1721.1/7618
Thu, 25 May 2017 15:35:07 GMT2017-05-25T15:35:07ZData-driven algorithms for operational problems
http://hdl.handle.net/1721.1/108916
Data-driven algorithms for operational problems
Cheung, Wang Chi
In this thesis, we propose algorithms for solving revenue maximization and inventory control problems in data-driven settings. First, we study the choice-based network revenue management problem. We propose the Approximate Column Generation heuristic (ACG) and Potential Based algorithm (PB) for solving the Choice-based Deterministic Linear Program, an LP relaxation to the problem, to near-optimality. Both algorithms only assume the ability to approximate the underlying single period problem. ACG inherits the empirical efficiency from the Column Generation heuristic, while PB enjoys provable efficiency guarantee. Building on these tractability results, we design an earning-while-learning policy for the online problem under a Multinomial Logit choice model with unknown parameters. The policy is efficient, and achieves a regret sublinear in the length of the sales horizon. Next, we consider the online dynamic pricing problem, where the underlying demand function is not known to the monopolist. The monopolist is only allowed to make a limited number of price changes during the sales horizon, due to administrative constraints. For any integer m, we provide an information theoretic lower bound on the regret incurred by any pricing policy with at most m price changes. The bound is the best possible, as it matches the regret upper bound incurred by our proposed policy, up to a constant factor. Finally, we study the data-driven capacitated stochastic inventory control problem, where the demand distributions can only be accessed through sampling from offline data. We apply the Sample Average Approximation (SAA) method, and establish a polynomial size upper bound on the number of samples needed to achieve a near-optimal expected cost. Nevertheless, the underlying SAA problem is shown to be #P hard. Motivated by the SAA analysis, we propose a randomized polynomial time approximation scheme which also uses polynomially many samples. To complement our results, we establish an information theoretic lower bound on the number of samples needed to achieve near optimality.
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2017.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 173-180).
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/1721.1/1089162017-01-01T00:00:00ZOrganizational structural effects on technology transfer
http://hdl.handle.net/1721.1/108866
Organizational structural effects on technology transfer
Pudar, Nick J. (Nick Joseph)
Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1990.; Includes bibliographical references (leaves 111-115).
Mon, 01 Jan 1990 00:00:00 GMThttp://hdl.handle.net/1721.1/1088661990-01-01T00:00:00ZComputerization in the newspaper industry
http://hdl.handle.net/1721.1/108858
Computerization in the newspaper industry
Nitay, Benjamin; Zurr, Zeev
Thesis. 1976. M.S.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management.; Microfiche copy available in Archives and Dewey.; Includes bibliographical references.
Thu, 01 Jan 1976 00:00:00 GMThttp://hdl.handle.net/1721.1/1088581976-01-01T00:00:00ZMultiserver queueing systems in heavy traffic
http://hdl.handle.net/1721.1/108834
Multiserver queueing systems in heavy traffic
Eschenfeldt, Patrick Clark
In the study of queueing systems, a question of significant current interest is that of large scale behavior, where the size of the system increases without bound. This regime has becoming increasingly relevant with the rise of massive distributed systems like server farms, call centers, and health care management systems. To minimize underutilization of resources, the specific large scale regime of most interest is one in which the work to be done increases as processing capability increases. In this thesis, we characterize the behavior of two such large scale queueing systems. In the first part of the thesis we consider a Join the Shortest Queue (JSQ) policy in the so-called Halfin-Whitt heavy traffic regime. We establish that a scaled process counting the number of idle servers and queues of length two weakly converges to a two-dimensional reflected Ornstein-Uhlenbeck process, while processes counting longer queues converge to a deterministic system decaying to zero in constant time. This limiting system is similar to that of the traditional Halfin-Whitt model in its basic performance measures, but there are key differences in the queueing behavior of the JSQ model. In particular, only a vanishing fraction of customers will have to wait, but those who do will incur a constant order waiting time. In the second part of the thesis we consider a widely studied so-called "supermarket model" in which arriving customers join the shortest of d randomly selected queues. Assuming rate n[lambda]n Poisson arrivals and rate 1 exponentially distributed service times, our heavy traffic regime is described by [lambda]n 1 as n --> [infinity]. We give a simple expectation argument establishing that queues have steady state length at least i* = logd 1/1-[lambda]n with probability approaching one as n [infinity] 8. Our main result for this system concerns the detailed behavior of queues with length smaller than i*. Assuming [lambda]n converges to 1 at rate at most [square root of]n, we show that the dynamics of such queues does not follow a diffusion process, as is typical for queueing systems in heavy traffic, but is described instead by a deterministic infinite system of linear differential equations, after an appropriate rescaling.
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2017.; This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.; Cataloged from student-submitted PDF version of thesis.; Includes bibliographical references (pages 107-109).
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/1721.1/1088342017-01-01T00:00:00Z