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You searched for subject:(Arrival rate uncertainty). Showing records 1 – 3 of 3 total matches.

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University of Texas – Austin

1. -9814-857X. Experimentation with multiple sources of uncertainty.

Degree: PhD, Economics, 2018, University of Texas – Austin

I study experimentation under two types of uncertainty – the quality and profitability of a risky technology. The quality of the technology can be good or bad. If the quality is good, then payoffs arrive at the jump times of the standard Poisson process. If the technology is bad it does not generate payoffs. Payoffs are stochastic and the sizes of the realizations depend on the underlying state of the economy. Some payoffs reveal the state completely, others do not. First, I consider an experimenter who chooses an irreversible exit time. I find that, after the first arrival of a payoff, the optimal stopping policy can be characterized by a cutoff belief about the true state of the economy. Before the first payoff, the stopping region of the experimenter is a subset of the space of beliefs about the technology's quality and profitability which cannot be characterized by cutoff beliefs. I find that the experimenter reacts differently to each source of uncertainty or risk, and that the most cost-effective subsidy for such an experimenter is an increase to his highest possible payoff. That is, the optimal subsidy makes the project riskier and subsidizes the experimenter when he is already performing well. Next, I consider an experimenter facing the same environment who also chooses the rate of the Poisson process after each observation of a payoff. While many of the results from chapter 1 carry through, I find that investment in the project in non-monotonic in the persistence of the states of the economy. Finally, I study an experimenter facing an environment similar to that in the first setting, but who has the option to irreversibly deploy his technology at scale, that is, to augment the payoffs in the long-run by making a large investment today. Here I find a rich set of investment and stopping policies, and that the optimal subsidy depends on the objective of the policy makers. Policy makers can encourage experimentation most efficiently by subsidizing the lowest payoff, and can encourage scaling the project by subsidizing the cost of investment. Advisors/Committee Members: Boyarchenko, Svetlana I. (advisor), Stinchcombe, Maxwell (committee member), Wiseman, Thomas (committee member), Feldman, Mark (committee member).

Subjects/Keywords: Optimal stopping; Endogenous arrival rate; Decision under uncertainty; Investment under uncertainty; Real options

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APA (6th Edition):

-9814-857X. (2018). Experimentation with multiple sources of uncertainty. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65837

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-9814-857X. “Experimentation with multiple sources of uncertainty.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed September 20, 2019. http://hdl.handle.net/2152/65837.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-9814-857X. “Experimentation with multiple sources of uncertainty.” 2018. Web. 20 Sep 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-9814-857X. Experimentation with multiple sources of uncertainty. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/2152/65837.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-9814-857X. Experimentation with multiple sources of uncertainty. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65837

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Texas A&M University

2. Alhuthali, Ahmed Humaid H. Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications.

Degree: 2010, Texas A&M University

Waterflood optimization via rate control is receiving increased interest because of rapid developments in the smart well completions and I-field technology. The use of inflow control valves (ICV) allows us to optimize the production/injection rates of various segments along the wellbore, thereby maximizing sweep efficiency and delaying water breakthrough. It is well recognized that field scale rate optimization problems are difficult because they often involve highly complex reservoir models, production and facilities related constraints and a large number of unknowns. Some aspects of the optimization problem have been studied before using mainly optimal control theory. However, the applications to-date have been limited to rather small problems because of the computation time and the complexities associated with the formulation and solution of adjoint equations. Field-scale rate optimization for maximizing waterflood sweep efficiency under realistic field conditions has still remained largely unexplored. We propose a practical and efficient approach for computing optimal injection and production rates and thereby manage the waterflood front to maximize sweep efficiency and delay the arrival time to minimize water cycling. Our work relies on equalizing the arrival times of the waterfront at all producers within selected sub-regions of a water flood project. The arrival time optimization has favorable quasi-linear properties and the optimization proceeds smoothly even if our initial conditions are far from the solution. We account for geologic uncertainty using two optimization schemes. The first one is to formulate the objective function in a stochastic form which relies on a combination of expected value and standard deviation combined with a risk attitude coefficient. The second one is to minimize the worst case scenario using a min-max problem formulation. The optimization is performed under operational and facility constraints using a sequential quadratic programming approach. A major advantage of our approach is the analytical computation of the gradient and Hessian of the objective which makes it computationally efficient and suitable for large field cases. Multiple examples are presented to support the robustness and efficiency of the proposed optimization scheme. These include several 2D synthetic examples for validation purposes and 3D field applications. Advisors/Committee Members: Datta Gupta, Akhil (advisor), Hill, A. Daniel (committee member), Mamora, Daulat D. (committee member), Bangerth, Wolfgang (committee member).

Subjects/Keywords: Optimal rate Control; geologic uncertainty; Time of Flight; arrival time; streamline-based sensitivity; stocastic form; min-max problem; water flooding.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Alhuthali, A. H. H. (2010). Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-456

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Alhuthali, Ahmed Humaid H. “Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications.” 2010. Thesis, Texas A&M University. Accessed September 20, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-456.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Alhuthali, Ahmed Humaid H. “Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications.” 2010. Web. 20 Sep 2019.

Vancouver:

Alhuthali AHH. Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-456.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alhuthali AHH. Optimal Waterflood Management under Geologic Uncertainty Using Rate Control: Theory and Field Applications. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-456

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

3. -5319-9514. Traffic signal control using queueing theory.

Degree: MSin Statistics, Statistics, 2018, University of Texas – Austin

Traffic signal control has drawn considerable attention in the literatures thanks to its ability to improve the mobility of urban networks. Queueing models are capable of capturing performance or effectiveness of a queueing system. In this report, SOCPs (second order cone program) are proposed based on different queueing models as pre-timed signal control techniques to minimize total travel delay. Stochastic programs are developed in order to handle the uncertainties in the arrival rates. In addition, the superiority of the proposed model over Webster’s model has been validated in a microscopic traffic simulation software named CORSIM. Advisors/Committee Members: Hasenbein, John J. (advisor), Machemehl, Randy B. (advisor).

Subjects/Keywords: Traffic signal control; Queueing theory; Queueing models; Urban network mobility; Queueing systems; Second order cone program; Pre-timed signal control techniques; Arrival rate uncertainty; Webster’s model

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-5319-9514. (2018). Traffic signal control using queueing theory. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67640

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-5319-9514. “Traffic signal control using queueing theory.” 2018. Masters Thesis, University of Texas – Austin. Accessed September 20, 2019. http://hdl.handle.net/2152/67640.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-5319-9514. “Traffic signal control using queueing theory.” 2018. Web. 20 Sep 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5319-9514. Traffic signal control using queueing theory. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2019 Sep 20]. Available from: http://hdl.handle.net/2152/67640.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5319-9514. Traffic signal control using queueing theory. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/67640

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

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