Research Project: Risk-Sensitive Policy Making for Populations
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Contributors
Funders
ID
EC.00057
Authors
Canbolat, Pelin Gülşah
Faculty Member
Publications
Risk-sensitive control of branching processes
(Taylor and Francis inc, 2021) Canbolat, Pelin Gülşah; Department of Industrial Engineering; Yes; College of Engineering
This article solves the risk-sensitive control problem for branching processes where the one-period progeny of an individual can take values from a finite set. the decision maker is assumed to maximize the expected risk-averse exponential utility (or to minimize the expected risk-averse exponential disutility) of the rewards earned in an infinite horizon. individuals are assumed to produce progeny independently, and with the same probability mass function if they take the same action. This article characterizes the expected disutility of stationary policies, identifies necessary and sufficient conditions for the existence of a stationary optimal policy that assigns the same action to all individuals in all periods, and discusses computational methods to obtain such a policy. are available for this article. See the publisher's online edition of IIE Transactions, datasets, Additional tables, detailed proofs, etc.
Pricing in a transportation station with strategic customers
(Wiley, 2017) Canbolat, Pelin Gülşah; Karaesmen, Fikri; Manou, Athanasia; Department of Industrial Engineering; Yes; College of Engineering
We consider a transportation station, where customers arrive according to a Poisson process, observe the delay information and the fee imposed by the administrator and decide whether to use the facility or not. a transportation facility visits the station according to a renewal process and serves all present customers at each visit. We assume that every customer maximizes her individual expected utility and the administrator is a profit maximizer. We model this situation as a two-stage game among the customers and the administrator, where customer strategies depend on the level of delay information provided by the administrator. We consider three cases distinguished by the level of delay information: observable (the exact waiting time is announced), unobservable (no information is provided) and partially observable (the number of waiting customers is announced). in each case, we explore how the customer reward for service, the unit waiting cost, and the intervisit time distribution parameters affect the customer behavior and the fee imposed by the administrator. We then compare the three cases and show that the customers almost always prefer to know their exact waiting times whereas the administrator prefers to provide either no information or the exact waiting time depending on system parameters.
