2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - V-shaped Sampling Based on Kendall-distance To Enhance
Optimization With Ranks
Haobin Li, Scientist, A*STAR, Institute of High Performance
Computing, 1 Fusionopolis Way, #16-16 Connexis North,
Singapore, 138632, Singapore,
Giulia Pedrielli, Loo Hay Lee, Ek Peng Chew, Chun-Hung Chen
Optimization over rank values has been of concern in multi-fidelity simulation
optimization. Specifically, Chen et al. (2015) proposes the concept of Ordinal
Transformation (OT) to translate multi-dimensional discrete optimization
problems into simpler single-dimension problem, where the dimension being
used is the rank in the ordinal space. In this paper we build on the idea of OT in
order to derive an efficient sampling algorithm to identify the solution with the
best rank in the settings of multi-fidelity optimization. We refer to this algorithm
as V-shaped, in which the concept of Kendall distance adopted in the machine
learning theory, is used to characterize solutions in the OT space.
4 - Bicycle-sharing With Reallocation Trucks And Private Exchange
Taipei YouBike System as Example
Hui-Chih Hung, National Chiao Tung University, Hsin-Chu, 300,
Taiwan, Jun-Min Wei, Ming-Te Chen
Subject to limited numbers of bicycles and docks, we consider trucks for bicycle
reallocation and mobile apps for private exchange in bicycle-sharing systems.
Trucks are hired to dynamically redistribute bicycles among unbalanced stations
and mobile apps are used to transfer bicycles among users without docks. This
allows bicycle exchange even when all docks are full. Three objectives are
studied: (1) maximizing the utilization of bicycles, (2) maximizing the net profit
of system, and (3) optimizing the fleet sizes of bicycles and trucks. Finally,
mathematical programming models are built and real data of Taipei YouBike
system from 2013 to 2015 are adopted for numerical study.
TD26
110B-MCC
Spectrum Auction
Invited: Auctions
Invited Session
Chair: Oleg Baranov, University of Colorado at Boulder, 256 UBC,
University of Colorado, Boulder, CO, 80309, United States,
1 - Efficient Dynamic Auction For U-shaped Returns
Oleg Baranov, Colorado,
When bidders have decreasing returns, the efficient dynamic auction is well-
known. Recently, Baranov et al. (2016) described an efficient dynamic auction for
bidders with increasing returns. In this paper, we design an efficient auction for
bidders with single-peaked returns. For auctions to buy, our setting includes one
of the most typical cost structures in economics. For auctions to sell, our setting is
a good approximation for single-band spectrum auctions.
2 - Obtaining The Final Channel Assignment In The Federal
Communications Commission’s First-ever Incentive Auction
Karla L Hoffman, Professor, George Mason University, Mail Stop
4A6, 4400 University Drive, Fairfax, VA, 20124, United States,
Brian Smith, Steven Charbonneau,
James Costa, Tony Coudert, Rudy Sultana
In this talk, we will discuss the procedure for determining the Final Channel
Assignment for U.S. and Canadian broadcasters at the conclusion of the
“Incentive Auction.” The FCC is utilizing a sequence of optimizations to create a
channel assignment that will be the least disruptive to both broadcasters and the
over the air television viewers. We will outline this sequence and explain how
this sequence satisfies the objectives of the FCC, Industry Canada and
broadcasters.
3 - Determining The Stations Not Needed In The Federal
Communication Commission’S First-ever Incentive Auction
Karla L Hoffman, George Mason University, System Eng and
Operations Research Dept, 4400 University Drive Mailstop 4a6,
Fairfax, VA, 22030, United States, ,
James Andrew Costa, Steven Charbonneau, Anthony Coudert,
Brian Smith, Rudy K Sultana
The FCC uses a novel descending-price auction to determine the spectrum to be
purchased from broadcasters. The auction is designed for stations to compete until
there are no channels available in the market. If a station always has a channel
available, they are not needed in the auction. An optimization procedure was
used to determine whether a station always had a channel available, and
therefore had no chance of winning in the auction.
4 - Combinatorial Land Assembly
Tzu-Yao Lin, University of Maryland,
We propose a reverse auction for real estate developers to acquire complementary
urban lands from multiple owners. Apart from the all-or-nothing mechanisms in
the previous literature, we determine the set of land parcels to be assembled in a
descending clock auction, which gradually lowers the offer to each remaining
owner until the trading condition is met. This mechanism is obviously
strategyproof for sellers. The optimal price adjustment trajectory is a solution for
the corresponding stochastic optimal control problem, which minimizes the
expected welfare loss from inefficient rejection.”
TD27
201A-MCC
Stochastic Modeling In Healthcare Operations
Sponsored: Manufacturing & Service Oper Mgmt
Sponsored Session
Chair: Carri Chan, Columbia Business School, New York, NY,
United States,
Co-Chair: Vahid Sarhangian, Columbia Business School, New York, NY,
United States,
1 - Identify Optimal Overflow Policies Using Approximate
Dynamic Programming
Pengyi Shi, Purdue University, Jim Dai
To alleviate Emergency Department congestion, boarding patients who wait to be
admitted to inpatient wards may have to be overflowed to a non-primary ward
when they wait too long. We develop approximate dynamic programming tools
to identify the optimal overflow policies under different system states.
2 - Yardstick Competition For Emergency Department Queues
Ozlem Yildiz, University of Rochester, Rochester, NY, United States,
Nicos Savva, Tolga Tezcan
We study whether an alternate pay-for-performance method can alleviate ED
overcrowding through incentivizing socially-desired ED capacity levels, although
the healthcare regulator does not know the capacity cost structure. Using
yardstick competition, we propose a regulatory scheme that achieves this using
the wait time and arrival rate information of each ED.
3 - Timing Of Hospital Discharges Matters
Jonathan Helm, Indiana University, ,
Rene Bekker
The mismatch in timing of arrivals and discharge processing in hospitals leads to a
census process that causes the hospital to experience significant congestion in the
middle of the day. This leads to a chaotic environment and major operational
efficiencies. In this research we formulate and analyze a stochastic census process
to investigate the effect of the timing of doctor’s discharge processing on inpatient
census levels and identify new approaches to discharge processing that can
alleviate congestion and also provide benefits to the patients being discharged
themselves.
4 - Dynamic Server Allocation In A Multiclass Queueing System With
Shifts: Nurse Staffing In Emergency Departments
Vahid Sarhangian, Columbia Business School, New York, NY,
United States, Carri Chan
Nurse staffing decisions in emergency departments (EDs) are typically assigned
weeks in advanced, which can create staffing imbalances as patient demand
fluctuates. In this work, we consider the potential benefits of assigning nurses to
different areas within an ED at the beginning of each shift. We study the problem
of optimal reassignment of nurses to areas by considering a multiclass queueing
model of the system. We analyze an associated fluid control problem and use the
solution to develop policies that achieve asymptotically optimal performance
under fluid-scaling for the original stochastic system. We find this additional
flexibility can substantially reduce waiting times for patients.
TD26