2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - How The Swine Flu Epidemic Spread: Lessons From The Data
Jussi Keppo, National University of Singapore, Mochtar Riady
Building, BIZ 1 8-69, 15 Kent Ridge Drive, Singapore, 119245,
Singapore, , Elena Quercioli, Lones Smith
Contagious diseases are passed on when contagious and susceptible individuals
meet. This paper introduces and explores a new matching game, characterized by
individuals meeting pairwise, possibly unwittingly passing along a disease in a
contagion-like fashion. We assume that individuals can expend costly effort to
avoid acquiring it. In this population game, efforts are strategic substitutes: The
harder other individuals try, the more lax one can be. We solve for the unique
Nash equilibrium when individuals are heterogeneous. We then estimate this
structural model and argue that it improves on the explanation of the data
without endogenous behavior.
4 - An Unbiased Measure Of Integrated Volatility In The
Frequency Domain
Fangfang Wang, University of Illinois at Chicago, 601 South
Morgan Street, Chicago, IL, 60607, United States,
This work studies the effect of market microstructure noise on volatility
estimation in the frequency domain. We propose a bias-corrected periodogram-
based estimator of integrated volatility. We show that the new estimator is
consistent and the central limit theorem is established under a general
assumption of the noise. We also provide a feasible procedure for computing the
bias-corrected estimator in practice. As a byproduct, we extract a consistent
frequency-domain estimator of the long-run variance of market microstructure
noise from high-frequency data.
5 - A Parallel Computation Of Characteristics Of Markov Chains With
“Islands” And “Ports”
Amod Basnet, University of North Carolina-Charlotte,
9201 University City Blvd, Fretwell, Charlotte, NC, 28262,
United States, Isaac M Sonin
We present a new algorithm to calculate the invariant distribution of a large
Markov chain (MC) whose state space is partitioned into “islands” and “ports”. An
island is a group of states with potentially many connections inside of the island
but a relatively small number of connections between islands. The states
connecting different islands are called “ports”. Our algorithm is developed in the
framework of the “state reduction approach”, but the special structure of our MCs
allows for computations to be performed in parallel. Additional problems for such
MCs, including computation of a Fundamental matrix, optimal stopping, and the
case of small transitions between islands are also analyzed.
WB77
Legends E- Omni
Opt, Integer Programing VI
Contributed Session
Chair: Andrea L. Arias, Graduate Student, Texas Tech University,
4425 82nd Street, Apt 2258, Lubbock, TX, 79424, United States,
1 - A Branch And Price Approach For Deployment Of Multi-tier
Software Services In Clouds
Bjorn Nygreen, Retired, Dept. of Ind. Econ. & Techn.
Management, NTNU, Trondheim, NO 7491, Norway,
, Anders Nordby Gullhav
This talk considers a problem of a cloud service provider (SP) that offers a set of
applications to its end-users. In short, the SP seeks to find the minimum cost
deployment of its services on an infrastructure consisting of a private and public
cloud, while maintaining a certain quality of service. We propose to solve the
problem using branch and price, where the sub problem is solved both by a MIP
solver and a heuristic label-setting algorithm. Our results show the benefits of
using the heuristic in addition to the exact MIP solver.
2 - Project Scheduling And Multi-skill Workforce Assignment For
Property Management Applications
Anthony Vatterott, Assistant, University of Missouri Saint Louis,
1 University Boulevard, Saint Louis, MO, 63121, United States,
Haitao Li, Norman Keith Womer
We present a new optimization framework to schedule, assign and route
maintenance tasks with a multi-skilled workforce. Mixed integer programming
methods are applied to obtain effective and efficient solutions to advance the
state-of-the-art of property management. Practical emphasis on job priority, skill
development and knowledge transfer are considered to form the temporal, spatial
and resource constraints while minimizing the total cost of project delivery.
3 - Optimal Selection Of Parsimonious Arima Forecasting Models
George G Polak, Professor, Wright State University, 227 Rike Hall,
Raj Soin College of Business, Dayton, OH, 45435, United States,
, Bogdan C Bichescu
In a parsimonious ARIMA Forecasting model the total number of terms chosen is
constrained, and treatment for nonstationarity is limited to differencing of a pre-
specified order. Accordingly, a term for non-stationary variation is included along
with autoregressive, moving average and white noise terms in a decomposition of
the time series. Mixed integer quadratic optimization problems are then
formulated for prescribing model parameters. Walsh functions and Haar wavelets
are employed to represent white noise and non-stationary variation, respectively.
4 - A Comparative Analysis Of MILP Formulations For The
Multi-family Capacitated Lot-sizing Problem (MFCISP)
Andrea L. Arias, Graduate Student, Texas Tech University,
4425 82nd Street, Apt 2258, Lubbock, TX, 79424, United States,
Andrea L. Arias, Graduate Student,
P. Universidad Católica de Valparaíso, Valparaíso, Chile,
Ricardo A. Gatica
The MFCLSP is a variant of the CLSP with setup times in which items are
organized into families. We present three MILP models for the MFCLSP (TRAD, LI
and RC), and develop a comparative analysis in order to evaluate their
performance using Cplex. Since solving large-scale problems has been shown to
consume a great amount of computational time (very unviable for application
purposes), we examine the performance of the formulations under solving time
constraints. The results show a major advantage for both LI and RC regarding to
linear relaxation bounds, and that RC performs much better in terms of
computational time to obtain the first feasible solution, yielding at the same time,
very good optimality gaps.
WB78
Legends F- Omni
Opt, Metaheuristics II
Contributed Session
Chair: Clara Novoa, Associate Professor, Texas State University, 601
University Dr, San Marcos, TX, 78666, United States,
1 - Information Supply Chain Optimization With Bandwidth
Limitations
Michael Hirsch, ISEA TEK, LLC, 3283 Hickory Lane,
Longwood, FL, 32779, United States, ,
Hector Juan Ortiz-Pena
Workflow management systems allow for visibility, control, and automation of
many business processes. Recently, non-business domains have taken an interest
in the management of workflows, and the optimal assignment and scheduling of
workflow tasks to users across a network. This research aims at developing a
rigorous mathematical programming formulation of the workflow optimization
problem. The resulting formulation is non-linear, but a linearized version is
produced. Three heuristics are developed to find solutions efficiently.
Computational experiments are presented and analyzed, comparing solutions to
the original linearized formulation with the three heuristics.
2 - An Intelligent Production Control System For Automotive Parts
Manufacturing With A CPS Approach
Jun Kim, Sungkyunkwan University, Suwon, Korea, Republic of,
, Hyun Jung Kim
This paper examines an intelligent production control system for automotive parts
manufacturing based on a cyber-physical systems (CPS) approach. We propose a
CPS-based operations monitoring platform that helps decision-making processes
in production management such as predicting undesirable events and reacting to
such problems in advance. Various issues in designing and implementing a CPS
platform for engine piston manufacturing processes are addressed.
3 - An Efficient Heuristic For The Capacitated Lot Sizing Problem
With Setup Carryover And Splitting
Srimathy Mohan, Associate Professor, Arizona State University,
Department of Supply Chain Management, W.P. Carey School Of
Management, Phoenix, AZ, 85069-7100, United States,
Cheng-Lung Chen, Muhong Zhang
We present a new formulation for the Capacitated Lot Sizing Problem with Setup
Carryover and Setup Splitting. Setup carryover transfers a completed machine
setup from one period to the next. Setup splitting completes a setup across period
boundaries. We present a Fix-and-Optimize heuristic that is easy to adapt for
model extensions. Our extensive experimentation shows that the heuristic
produces results within 6% and 8% of optimality for problems without and with
demand backlogging, respectively.
WB77