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INFORMS Philadelphia – 2015
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3 - Discussant’s Presentation
Yu Ding, Professor, Texas A&M University, ETB 4016, MS 3131,
College Station, TX, United States of America,
As a discussant in this Technometrics special issue session on system informatics, I
will present my understanding of strengths and weaknesses of the two papers
selected by Technometrics editor for this session. I will also discuss other related
research problems on the similar topics.
TC75
75-Room 204B, CC
IBM Research Best Student Paper Award III
Sponsor: Service Science
Sponsored Session
Chair: Ming-Hui Huang, National Taiwan University, Taiwan - ROC,
1 - Best Student Paper Competitive Presentation
Ming-Hui Huang, National Taiwan University, Taiwan - ROC,
Finalists of the IBM Research Best Student Paper Award present their research
findings in front of a panel of judges. The judging panel will decide the order of
winners, which will be announced during the business meeting of the Service
Science Section at the Annual Conference.
2 - Efficient Information Heterogeneity in a Queue
Yang Li,Rotman School of Management, University of Toronto,
105 St. George Street, Toronto ON M5S3E6, Canada,
, Ming Hu
How would the growing prevalence of real-time delay information affect a service
system? We consider an M/M/1 queueing system in which only a fraction of
customers are informed about real-time delay. Surprisingly, we find that system
throughput and social welfare can be unimodal in the fraction of informed
customers.
3 - Scheduling and Pricing Services for Online Electric Vehicle
Charging
Mark Nejad,Assistant Professor, University of Oklahoma,
Industrial and Systems Engineering, Norman OK, United States of
America, , Ratna Babu Chinnam, Daniel
Grosu, Lena Mashayekhy
We design mechanisms for EV charging services in online settings. We prove that
our proposed mechanisms are incentive compatible, that is, truthful reporting of
price and the amount of charging is a dominant strategy for self-interested EV
drivers. Our preemption-aware charging mechanisms allow providers to manage
fluctuations in renewable energy production.
4 - Scheduling with Testing
Thomas Magnanti,Institute Professor, MIT, 77 Massachusetts
Avenue, 32-D784, Cambridge MA 02139, United States of
America, , Retsef Levi, Yaron Shaposhnik
We study a new class of scheduling problems that captures a common tradeoff
between using resources for processing jobs, and investing resources to ‘test’ jobs
and learn more about their uncertain attributes. This can inform future decisions,
but also delay service. We derive intuitive structural properties of the optimal
policies, and use a new cost-accounting scheme to devise a surprisingly low
dimensional dynamic programming formulation, which ultimately leads to an
FPTAS.
5 -Trading Time in a Congested Environment
Luyi Yang,Doctoral Student, University of Chicago Booth School
of Business, Chicago, IL, United States of America,
Laurens Debo, Varun Gupta
We propose a time-trading mechanism, mediated by a revenue maximizing
broker, in which customers privately informed about their waiting costs mutually
agree on the ordering in a queue via trading positions. To that end, we show that
the broker can implement an auction with a trade-participation fee and two trade
restriction prices on customer bids. Under the optimal auction, there is partial
pooling in the bidding strategies and therefore customers are not strictly
prioritized.
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76-Room 204C, CC
Advances in Stochastic Simulation
Sponsor: Simulation
Sponsored Session
Chair: Henry Lam, University of Michigan, 1205 Beal Ave., Ann Arbor,
MI, United States of America
1 - Risk Assessment for Input Uncertainty
Helin Zhu, School of Industrial and Systems Engineering, Georgia
Institute of Technology, 755 Ferst Drive NW, Atlanta, GA, 30332,
United States of America, , Enlu Zhou
When simulating a complex stochastic system, the behavior of the output
response depends on the input parameter estimated from finite real-world data,
and the finiteness of data brings input uncertainty to the output response. Risk
assessment for input certainty, which quantifies the extreme behavior of the
mean output response, is extremely important. In the present paper, we introduce
the risk measures for input uncertainty and study the corresponding estimators.
2 - Projected Directional Derivatives for High Dimensional
Gradient Estimation
Raghu Pasupathy, Associate Professor, Department of Statistics,
Purdue University, 250 N University Street, West Lafayette, IN,
47907, United States of America, ,
Boqian Zhang
We present a method to estimate gradients in high dimensions by projecting
randomly generated directional derivatives onto the various axes. We discuss
theoretical properties and sampling measures that minimize the resulting
estimator’s error norm. The method appears particularly relevant in high
dimensions since only two observations are needed for a complete gradient
estimator.
3 - Perfect Sampling of GI/GI/C Queues
Yanan Pei, Columbia University, 500 W. 120th St, Mudd 313,
New York, NY, 10027, United States of America,
, Jose Blanchet, Jing Dong
We introduce the first class of perfect sampling algorithms for the steady-state
distribution of multi-server queues with general inter-arrival time and service
time distributions. Our algorithm is built on the classical dominated coupling from
the past protocol using a coupled multi-server vacation system as the upper
bound process. The algorithm has finite expected termination time with mild
moment assumptions on the inter-arrival time and service time distributions.
4 - Rare Event Simulation in the Neighborhood of a Rest Point
Konstantinos Spiliopoulos, Assistant Professor, Boston University,
Department of Mathematics and Statistics, 111 Cummington
Mall, Boston, MA, 02215, United States of America,
We construct efficient importance sampling Monte Carlo schemes for finite time
exit probabilities in the presence of rest points. The main novelty of the work is
the inclusion of rest points in the domain of interest. We motivate the
construction of schemes that perform well both asymptotically and non-
asymptotically. We concentrate on the regime where the noise is small and the
time horizon is large. Examples and simulation results are provided. Joint work
with Paul Dupuis and Xiang Zhou.
TC77
77-Room 300, CC
Logistics II
Contributed Session
Chair: Fateme Fotuhiardakani, Data Scientist, TMW Systems, 6085
Parkland Blvd, Mayfield Heights, OH, 44124, United States of America,
1 - Using Heuristics to Solve the Container Loading Problem
Focusing on Priority Levels and Utilization
Crystal Wilson, Clemson University, 6 Natalie Ct., Greer, SC,
29651, United States of America, ,
Mary Beth Kurz
Just-in-time manufacturers need the parts to arrive to the facility by a scheduled
time to keep the assembly line moving smoothly. How small containers, such as
parts, are loaded onto a larger container is a special type of packing problem. This
research will focus on creating a heuristic that creates loading patterns that
balances priority levels, while also maximizing the utilization of the container
with respect to the weight and cube.
TC75