2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - A New Mathematical Formulation For Choice-based
Optimization Problems
Shadi Sharif Azadeh, Ecole Poloytechnique Federale de Lausanne,
38 Route de la Condemine, Lausanne, 1030, Switzerland,
Meritxell Pacheco, Michel Bierlaire
The mathematical modeling of choice behavior has been an active field of
research. Their complexity leads to mathematical formulations that are highly
non convex in the explanatory variables especially when they are integrated
inside an MILP to take into account both supply and demand constraints. We
propose a new mathematical modeling that can simplify nonlinear and
nonconvex choice-based optimization models with the help of simulation inside
an MILP framework. We have tested the model on a real case study and
computational results testify the goodness of this modeling approach.
4 - Microsoft Excel Evolutionary Solver And Resource Constrained
Project Scheduling
Norbert Trautmann, Professor, University of Bern, FM Quantitative
Methoden, Schuetzenmattstrasse 14, Bern, 3012, Switzerland,
, Mario Gnägi
We discuss how to apply the evolutionary solver contained in Microsoft Excel’s
Solver Add-in to the resource-constrained project scheduling problem (RCPSP).
Combining a novel spreadsheet-based implementation of an appropriate
schedule-generation scheme with the evolutionary solver provides surprisingly
good schedules.
5 - An Exact Algorithm For The Demand Constrained 0-1
Knapsack Problem
Christopher John Wishon, PhD Candidate, Arizona State
University, Tempe, AZ, United States, ,
J. Rene Villalobos
The demand constrained KP is a variant of the binary KP in which a weighted
summation of the variables must exceed a given threshold in addition to the
standard KP constraint. The first exact algorithm for solving this variant is
presented which utilizes a reduction routine prior to a breadth-first expanding
core approach for determining the remaining variables. A polynomial time
solution to the continuous relaxation is employed such that high quality, integer
Lagrangian and surrogate relaxations are solved to obtain tight upper bounds.
Performance is tested using computational experiments with results
demonstrating that the algorithm can outperform commercial software.
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Broadway E- Omni
Health Care, Public III
Contributed Session
Chair: Philip F. Musa, Associate Professor and Programs Director,
The University of Alabama at Birmingham (UAB), P.O. Box 55544,
Birmingham, AL, 35255, United States,
1 - Micro-decision Patterns In Prescription Data: An Investigation Of
Local And Non-communicable Diseases Among Vertically
Differentiated Social
W. Art Chaovalitwongse, University of Arkansas, Fayetteville, AR,
Contact: Praowpan Tansitpong, Apirak
Hoonlor
This study explores electronic healthcare database in defining decision patterns in
prescribed medicines among government-subsidized benefit schemes in Thailand.
The analysis focuses on three major non-communicable diseases (diabetes, can-
cer, and cardiovascular) and three local diseases located in inpatient and outpa-
tient database. The study separates uniform prescription patterns in all three
schemes from non-uniform patterns and predicts brand and amount of dosage to
be prescribed to other diseases. The findings also suggest prescription priority in
medicine inventory control.
2 - Minimizing Radiology Error By Improving Staff Scheduling
Mahdi Nasereddin, Penn State- Berks, Tulpehocken Road, P.O. Box
7009, Reading, PA, 19610-6009, United States, ,
Michael Bartolacci, Michael Bruno
Errors are sometimes made when reading radiology charts. A 2001 study reported
that depending on the area, the radiology error rate is between 2 - 20%. A team
of researchers at the Penn State University is currently studying how to minimize
radiology error rate. In this study, the relationship between under-staffing and
radiology errors is being investigated.
3 - Evaluating Policy Options For Improving Access To Dental Care
For Children In Georgia
Benjamin Johnson, Georgia Institute of Technology,
3245 Wellbrook Drive, Loganville, GA, 30052, United States,
, Nicoleta Serban, Paul Griffin,
Susan Griffin
Policies regulating dental providers differ by state. Policies in Georgia are
compared to similar policies in other states to estimate the impact of each policy
on access to dental care. Policy changes are then evaluated to show the impact a
new policy could have on improving access to children in Georgia.
4 - Obesity In Africa: The Ultimate Black Belt Region Bursting
At The Seams
Philip F. Musa, Associate Professor and Programs Director, The
University of Alabama at Birmingham (UAB), P. O. Box 55544,
Birmingham, AL, 35255, United States,
What are the root causes of obesity as a Public Health epidemic across Africa? We
present comparisons of demographics of those most predisposed to this precursor
to chronic comorbidities in developed countries such as the United States and the
least developed regions such as Sub-Saharan Africa. It was only fairly recently
that mortality rates due to chronic diseases surpassed those due to infectious
diseases in industrialized countries. While that has not yet occurred in Africa,
there is evidence that the burden due to chronic diseases associated with obesity
may soon eclipse those affiliated with infectious diseases. Public Health
interventions are suggested in this paper.
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Broadway F- Omni
Opt, Integer Programming I
Contributed Session
Chair: Vishnu Vijayaraghavan, Texas A&M University, 400 Nagle Street,
College Station, TX, 77840, United States,
1 - A Branch-and-cut Algorithm Using Two-period Relaxations For
Big-bucket Lot-sizing Problems
Kerem Akartunali, Senior Lecturer, Strathclyde Business School,
Dept. of Management Science, University of Strathclyde, Glasgow,
G4 0GE, United Kingdom, ,
Mahdi Doostmohammadi, Ioannis Fragkos
We study the polyhedral structure of the two-period subproblem proposed by
Akartunali et al. (2016). Based on two relaxations of the subproblem, we propose
new families of valid inequalities and present facet-defining conditions. These
inequalities are lifted to the original space of the two-period subproblem, and
they also inspire the derivation of a new family of inequalities defined in the
original space. We exploit the structural similarities of the different families in
order to design an efficient separation algorithm, and embed it in a modern
branch-and-cut solver.
2 - Prescriptive Analytics To Improve E-warehouse Operations
Fatma Gzara, Associate Professor, University of Waterloo,
200 University Avenue W, Waterloo, ON, N2V 2N1, Canada,
We use data for an e-commerce warehouse characterized with high order
volumes, significant seasonality, and a large number of SKUs. Based on extensive
descriptive data analysis, the packing operation is identified as a major cause for
long order completion times. We develop an optimization model and solution
methods based on decomposition and heuristics to optimize order packing. We
validate our results using industry data.
3 - Finding Optimal Solutions For Emergency Evacuation By A
Dynamic Programming Approach Based On State-space-time
Network Representation
Lei Bu, Institute for Multimodal Transportation, Jackson, MS,
United States, , Feng Wang, Xuesong Zhou
Based on a representation of state-space-time network, a formulation is proposed
to optimize dynamic vehicle routes strategy in an emergency evacuation. The
proposed integer linear programming formulation could effectively build the
modeling representation of time status, evacuation demand, node capacity and
traffic volume change constraints through a multi-dimensional network with an
objective function to minimize total travel cost of visiting all nodes. Bellman-
Held-Karp algorithm working as a dynamic programming algorithm is utilized to
solve the problem. Two scale levels of networks in Mississippi State are tested
using the model and algorithm proposed to verify the effectiveness.
4 - A Modified Cutting Plane Algorithm For Inverse Mixed Integer
Linear Programming Problems
Vishnu Vijayaraghavan, Texas A&M University, 400 Nagle Street,
College Station, TX, 77840, United States,
Kiavash Kianfar, Andrew J Schaefer
Given a feasible solution to an optimization problem, the purpose of an inverse
optimization problem is to minimally perturb the cost vector to make this feasible
solution an optimal one. Inverse optimization for mixed integer programming is
particularly challenging and previously a cutting plane algorithm has been
proposed. In this paper we present a modification of this algorithm which
significantly reduces the number of iterations, and hence run-time, until
termination.
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