Informs 2015

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INFORMS Philadelphia – 2015
350
TD15
15-Franklin 5, Marriott
Capacity Management in Healthcare Operations
Sponsor: Optimization in Healthcare
Sponsored Session
Chair: Sandeep Rath, PhD Candidate, UCLA Anderson, B501 Gold Hall,
UCLA Anderson, Los Angeles, CA, 90024, United States of America,
1 - Workforce Optimization with Patient Volume Variations and
Scheduling Pattern Generation for Hospital
Xuanqi Zhang, Philips Research North America, 345 Scarborough
Rd, Briarcliff Manor, NY, 10510, United States of America,
, Jingyu Zhang
A two-stage model is created to optimize hospitals’ workforce which directly
affects hospital cost and patients satisfaction. The model uses simulation-based
stochastic optimization and heuristics to reduce staffing cost, avoid understaffing
and improve scheduling efficiency. The two-stage solution mechanism helps
diminish the gap between staffing optimization research and hospital scheduling
practice. Results were delivered to and tested in hospitals.
2 - Integer Programming Model to Solve Bloodmobiles
Routing Problem
Grisselle Centeno, Associate Professor, Univ. of South Florida,
4202 E. Fowler Ave., Tampa, FL, 33620, United States of America,
Serkan Gunpinar
Blood is a scarce and perishable resource. Approximately 80% of the blood
donations are handled remotely via bloodmobiles. Blood center must determine
the number of bloodmobile units to operate, and designate their daily location(s)
to avoid shortfalls. In this study, a vehicle routing problem is developed using IP.
Optimal routing for each bloodmobile is identified using CPLEX solver & column
generation algorithm. Computational results will be discussed.
3 - A Binary Integer Programming Approximation for Vaccine
Vial Distribution
Zahra Azadi, Clemson University, 854 Issaqueena Trl. Apt#902,
Central, SC, 29630, United States of America,
, Sandra Eksioglu
One of the challenges faced by health care providers is designing an inventory
replenishment policy for vaccines to ensure a successful immunization of patients
while minimizing purchasing, inventory and wastage costs. Wastage incurs when
doses are disposed from opened vials after their safe use time. We propose an (s,
S) policy which determines the vial size, the reorder quantity, and the order up to
point which optimizes system-wide costs.
TD16
16-Franklin 6, Marriott
Inverse Optimization
Sponsor: Optimization/Linear and Conic Optimization
Sponsored Session
Chair: Daria Terekhov, Concordia University, 1455 De Maisonneuve
Blvd. W., Montreal, Canada,
1 - A Goodness-of-fit Measure for Inverse Optimization
Daria Terekhov, Concordia University, 1455 De Maisonneuve
Blvd. W., Montreal, Canada, ,
Taewoo Lee, Timothy Chan
Using an analogy between regression and inverse optimization, we develop a
framework for cost function estimation in linear optimization consisting of a
general inverse optimization model and a corresponding goodness-of-fit metric.
We propose several natural specializations of the framework that evaluate
goodness-of-fit in both the space of decisions and objective value.
2 - Inverse Optimization for the Analysis of Competitive Markets
Michael Pavlin, Wilfrid Laurier University, 75 University Ave,
Waterloo, ON, Canada, , John Birge, Ali Hortacsu
We consider use of inverse optimization as an empirical tool for uncovering
unobservable parameters in competitive markets. In particular, we apply these
techniques to the recovery of transportation and production cost parameters in
natural gas markets.
3 - Three Newsvendor Models for Capacity Allocation
Sam Choi, Assistant Professor, Shenandoah University, 1460
University Dr., Winchester, VA, 22601, United States of America,
We propose three newsvendor models to allocate capacity under uncertainty:
inverse newsvendor, sequential newsvendor, and inverse sequential newsvendor
models. The inverse newsvendor model tries to find optimal demand size under
capacitated environment. The sequential newsvendor model deals with optimal
time durations given that demand sizes. Lastly, the inverse sequential newsvendor
model determines optimal demand sizes given that time durations. We apply
three models to healthcare settings.
TD17
17-Franklin 7, Marriott
Routing and Multidimensional
Assignment Applications
Sponsor: Optimization/Network Optimization
Sponsored Session
Chair: Jose Walteros, University at Buffalo, 342 Bell Hall, Buffalo, NY,
United States of America,
1 - Gasoline Replenishment and Routing Problem with Variable
Demands and Time Windows
Yan Cheng Hsu, University at Buffalo (SUNY), 412 Bell Hall,
Buffalo, NY, 14228, United States of America,
Rajan Batta, Jose Walteros
An iterative procedure is presented to tackle the gasoline replenishment problem
of gas stations and vehicle routing problem. The problem is formulated as
inventory model with a send-back cost due to the gasoline delivery property that
gas stations should accept ordered quantity completely, to find order quantity and
time window of gas stations, minimizing expected total cost, and as MIP model to
resolve vehicle routing problem, maximizing total profit for transporters.
2 - Solving Multidimensional Assignment Problems with
Combinatorial Decomposable Cost Functions
Hadi Feyzollahi, State University of New York at Buffalo,
316 Bell Hall, Buffalo, NY, United States of America,
Jose Walteros
We consider several variants of the multidimensional assignment problem (MAP)
where the costs of the optimal assignments are calculated by solving
combinatorial optimization problems. We focus our attention on the cases where
the assignments represent optimal TSP tours, spanning trees, and cliques. We
formulate these MAPs as set partitioning problems and solve them via branch and
price. We develop specific algorithms for solving the corresponding subproblems
for each of the aforementioned cases.
3 - Location-capacity-routing Problem of All-electric
Delivery Vehicles
Nan Ding, University of Buffalo, Buffalo, NY, United States of
America, , Rajan Batta
All-electric truck adoption becomes one of the main addressees of green logistic
activities, with challenges of limited driving range and long charging time to route
these trucks. This problem aims to handle the challenges of congestion and
waiting at the charging stations. A joint location-capacity-routing (LCR) problem
to determine the optimal location and capacity of charging stations is formulated
and a meta-heuristic approach is proposed to solve this LCR problem.
4 - Large-scale Neighborhood Search for the Multi-dimensional
Assignment Problem
Alla Kammerdiner, New Mexico State University, P.O. Box 30001,
MSC 4230, Las Cruces, NM, 88003, United States of America,
Charles Vaughan
The multi-dimensional assignment problem is an NP-hard problem in high-
dimensional combinatorial optimization. This problem arises in the military
surveillance applications (e.g. sensor data fusion and target tracking) and in
healthcare for ranking exposures to falls. We propose and investigate a new large-
scale search algorithm for this computationally difficult problem. We evaluate the
performance of new algorithm on various instances and compare it to other state-
of-the-art procedures.
TD15