2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
316
4 - Influence Maximization In Linear Threshold And Triggering Models
Po-Ling Loh, UW - Madison, Madison, WI, 53717, United States,
We discuss upper and lower bounds for the influence of a set of nodes in certain
types of contagion models. We quantify the gap between our upper and lower
bounds in the case of the linear threshold model and illustrate the gains of our
upper bounds for independent cascade models in relation to existing results.
Furthermore, our lower bounds are monotonic and submodular, implying that a
greedy algorithm for influence maximization is guaranteed to produce a
maximizer within a $\left(1-\frac{1}{e}\right)$-factor of the truth. Our bounds
may be evaluated efficiently, leading to an attractive, highly scalable algorithm for
influence maximization with rigorous theoretical guarantees.
TC41
207C-MCC
Quantitative Risk Management
Sponsored: Financial Services
Sponsored Session
Chair: Abel Cadenillas, University of Alberta, Edmonton, AB, Canada,
1 - Systemic Influences On Optimal Equity-credit Investment
Christoph Frei, University of Alberta,
Agostino Capponi
Recent events showed that the dependence structure of financial markets is more
complex than what is captured by classical models. For example, the financial
instability of some companies spread out to affect other companies. We analyze
how such systemic influences are reflected in optimal investment decisions. To
this end, we introduce a model with dependence structure between market risk
and default risk of the companies. An investor can use stocks and credit default
swaps (CDSs) to participate in the market. We derive an explicit expression for
the optimal investment strategy in stocks and CDSs. An empirical analysis reveals
the critical role of systemic risk in portfolio monitoring.
2 - Optimal Governement Debt Ceiling
Abel Cadenillas, University of Alberta,
Ricardo Huaman-Aguilar
Motivated by the debt crisis in the world, we apply methods of stochastic control
to obtain an explicit formula for the optimal government debt ceiling.
3 - Optimal Cash Holdings Under Funding Risk
Andreea Minca, Cornell University,
This talk explores a one-period model for a firm that finances itsoperations
through debt provided by heterogeneous creditors. Creditorsdiffer in their beliefs
about the firm’s investment outcomes. We showthe existence of Stackelberg
equilibria in which the firm holds cashreserves in order to provide incentives for
pessimistic creditorsto invest in the firm. We find interest rates and cash holdings
tobe complementary tools for increasing debt capacity. In markets witha high
concentration of capital across a small interval of pessimisticcreditors or by a few
large creditors, cash holdings is the preferredtool to increase the debt capacity of
the firm.
4 - EM Algorithm and Stochastic Control
Steven Kou, National University of Singapore,
We propose an algorithm called EM-Control (EM-C) algorithm to solve multi-
period finite-time horizon stochastic control problems. Generalizing the idea of
the EM algorithm, the EM-C algorithm sequentially updates the control parame-
ters in each time period in a backward manner. The EM-C algorithm has monot-
onicity of performance improvement in every iteration. We apply the EM-C algo-
rithm to solve stochastic control problems in real business cycle and monopoly
pricing of airline tickets. This is a joint work with Xianhua Peng and Xingbo Xu.
TC42
207D-MCC
Revenue Management with Advertising Applications
Sponsored: Revenue Management & Pricing
Sponsored Session
Chair: John G Turner, University of California - Irvine, Room SB2 338,
Irvine, CA, 92697-3125, United States,
1 - The Bid Adjustment Problem In Search Advertising
Mustafa Sahin, University of Maryland,
, Subramanian Raghavan,
Abhishek Pani, Abhishek Pani
We discuss the problem faced by the advertiser in search advertising in the
presence of bid adjustments. Recent developments in search advertising created a
setting in which the advertiser can target specific demographics by using bid
adjustments. We propose a Mixed Integer Programming formulation for the
problem. However, the problem is computationally hard and cannot be solved by
a generic commercial solver for any instance of reasonable size. Therefore, we
offer heuristic approaches to tackle the intractability issues and present results on
hard instances.
2 - Analysis Of Competitive Pricing With Multiple Overlapping
Competing Bids In Revenue Management
Goutam Dutta, Professor, Indian Institute of Management, House
No 407, Iima Old Campus, Vastrapur, Ahmedabad, 380015, India,
We formulate the pricing problem from the point of view of one seller having one
or multiple competitors (say n). Based on past experience, we know the
distribution of bid prices of the competitors. We consider uniform and normal
distribution to describe the bid price of the competitors. The prices of the
competitors are mutually independent and the price ranges are either identical or
different and overlapping. We maximize the expected contribution of the seller.
Assuming the contribution as a linear function of price we find the conditions for
maximization of the expected contribution to profit in case of n bidders. Further,
we also compare the optimization results with simulation results.
3 - Markov Chain Models For Controlling The Frequency Distribution
Of Online Advertising
Seyed Ali Hojjat, University of New Hampshire, Durham, NH,
United States, John G Turner
Recent trends in online advertising show that explicit reach and frequency
specifications are more desired over aggregate impression or budget goals.
Depending on whether the frequency of ad serving to each user is measured over
a fixed timespan (e.g., the number of times each user is exposed to the ad within
each calendar week) or on a rolling basis (e.g., over any contiguous 24-hour
period throughout the campaign’s horizon), we propose an appropriate Markov
chain model for serving ads and investigate its properties in maintaining a desired
frequency distribution for an online ad campaign.
4 - Planning Online Advertising Using Lorenz Curves
John G Turner, University of California - Irvine, Irvine, CA,
United States, , Miguel A Lejeune
Lorenz curves are commonly-used to depict dispersion; e.g., income inequality.
Motivated by online advertising campaigns that desire impressions spread over
targeted audience segments and time, we formulate a problem that minimizes
Gini Coefficients (area under the Lorenz curve), and develop a specialized
decomposition technique to solve instances quickly.
TC43
208A-MCC
Decision Making in Public Policy
Sponsored: Decision Analysis
Sponsored Session
Chair: Cameron MacKenzie, Iowa State University, Ames, IA,
United States,
1 - Hurricane Decision Simulator
Eva D Regnier, Naval Postgraduate School, ,
Cameron MacKenzie, Eric S Hodson
When threatened by a hurricane, Marines in New Orleans face a classic sequential
decision under uncertainty with regularly updated information, but few
opportunities to learn from experience. The Hurricane Decision Simulator allows
personnel to run experience key decisions in the context of many realistic
simulated storms, to develop a better understanding of the interrelated decisions
required, and a familiarity with the forecast products and their evolving
uncertainty. This talk highlights application of both “hard” and “soft” sides of
analytics in the development of the tool. This is the first hurricane training tool
that allows users to explore many different decision paths.
2 - Subsidizing Cybersecurity Information Sharing: A Game Between
A Government And N-Companies
Ali Pala, University at Buffalo, Buffalo, NY, 14260, United States,
Ali Pala, Turkish Military Academy, Devlet Mahallesi, Bakanlıklar,
Ankara, Turkey, , Jun Zhuang
More cybersecurity information sharing would lead to stronger resistance against
cyber-attacks in the presence of a cooperative and trustworthy sharing network.
Sharing cyber-attack information, however, could harm reputation, create
disadvantages against competitors and additional costs, and cause disclosing
vulnerabilities and some private information. In this research, we study what,
how, and to whom government incentives should be provided in order to
encourage and improve information sharing. We incorporate game theory and
agent-based simulation modeling to develop a dynamic decision support tool that
generates information sharing strategies in the face of strategic attackers.
TC41