Informs 2015

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INFORMS Philadelphia – 2015
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2 - Clickstream Big Data and “Delivery Before Order Making” for
Online Retailers
Haoxuan Xu, School of Management, Huazhong University of
Science and Technology, 1037 Luoyu Road, Hongshan District,
Wuhan, 430074, China, Yeming Gong,
Wilco Van Den Heuvel, Albert Wagelmans, Jinlong Zhang
Our research is inspired by a leading online retailer using clickstream big data to
estimate customer demand and then ship items to customers by a mode of
“Delivery Before Order Making” (DBOM) operational mode. Using clickstream
data to obtain advance demand information (ADI) in order quantities, we
integrate the forecasting with a single-item uncapacitated dynamic lot sizing
problem in a rolling-horizon environment. Using the simulated clickstream data,
we evaluate the performance of DBOM mode.
3 - Estimating Seasonality of E-commerce Sales
Abhay Jha, Walmart E-Commerce, 850 Cherry, San Bruno, CA,
United States of America,
The assortment of items in e-commerce includes a lot of items with short life-
span; hence the traditional methods of estimating seasonality per item by looking
at past years’ sales are not applicable here. We will formulate this problem as
maximizing the penalized likelihood of a state space model, where we penalize
the seasonality to have some plausible properties, and use the semantic
information about items to constrain similar items to have similar seasonality.
4 - A Simulation Framework of Consumer-to-Consumer Ecommerce
Business Model
Oloruntomi Joledo, University of Central Florida, 4000 Central
Florida Blvd, Orlando, FL, 32816, United States of America,
Luis Rabelo
In the past decade, ecommerce transformed the business models of many
companies.This paper proposes a modeling and simulation framework to
investigate how the actions of stakeholders in consumer-to-consumer ecommerce
affect the system performance as well as the business dynamics of the model. The
goal is to provide stakeholders with a decision making tool to assess the viability
and performance of the consumer-to-consumer business model.
5 - Higher Prices for Larger Quantities? Non-monotonic
Price-quantity Relations in B2b Markets
Wei Zhang, Assistant Professor, University of Hong Kong,
University of Hong Kong, Hong Kong, China,
We study a microprocessor company that has a limited capacity and negotiates
with each buyer for the price. Our analysis of their data reveals that larger
purchases do not always result in bigger discounts, and we show that the non-
monotonicity is rooted in how sellers value capacity. The value of residual
capacity may be initially convex and then concave. Such a value function is
sufficient to ensure a non-monotonic price-quantity relationship.
WC11
11-Franklin 1, Marriott
Optimization Integer Programming II
Contributed Session
Chair: Ioannis Fragkos, Post Doctoral Fellow, HEC Montreal,
3000 Chemin de la Cote-Sainte-Catherine, Montreal, Canada,
1 - A Computational Study of Two-Period Relaxations for
Big-Bucket Lot-Sizing Problems
Ioannis Fragkos, Post Doctoral Fellow, HEC Montreal,
3000 Chemin de la Cote-Sainte-Catherine, Montreal, Canada,
, Mahdi Doostmohammadi,
Kerem Akartunali
Lot-sizing problems form the backbone of most modern production planning
systems. Despite the significant advancements in optimization theory and
software, most methods used in practice lead to higher-than-optimal costs. In this
talk we investigate new classes of inequalities that are based on two-period
relaxations. We discuss separation procedures and a branch-and-cut
implementation. Computational experiments are promising, and show that the
proposed inequalities derive improved lower bounds.
2 - A Small-Order-Polynomial-Sized Linear Program for the Traveling
Salesman Problem with Tight Bounds
Mark Karwan, University at Buffalo, 342 Bell Hall, North
Campus, Buffalo, NY, 14260, United States of America,
Moustapha Diaby, Lei Sun
We present a polynomial-sized linear program for the n city TSP drawing upon
‘complex flow’ modeling ideas by the authors who used an O(n9)xO(n8) model.
Here we have only O(n5) variables and O(n4)constraints. We use an assignment
problem-based abstraction of tours not employing the traditional city-to-city
variables of the standard TSP formulation. We solved thousands of problems with
up to 26 cities using the simplex and barrier methods of CPLEX, consistently
obtaining all integer solutions.
3 - A Branch and Bound Approach to the Minimum K-enclosing
Ball Problem
Marta Cavaleiro, Rutgers University, 100 Rockefeller Rd.,
Piscataway, NJ, 08854, United States of America,
Farid Alizadeh
The minimum k-enclosing ball problem seeks the ball with smallest radius that
contains at least k of n given points. This problem is NP-hard. For the minimum
enclosing ball problem (requiring the ball to contain all points) there are both
primal and dual iterative algorithms that are very similar to the simplex method
for LP. We incorporate these methods into a branch and bound search to solve the
minimum k-enclosing ball problem. Some computational results will be
presented.
4 - Cutting Circles via Piecewise Milp
Steffen Rebennack, Colorado School of Mines, 1500 Illinois
Street, Golden, CO, United States of America,
In circle cutting, one computes an area minimizing rectangle hosting a given set
of circles. These circles are not allowed to overlap. This circle cutting problem is
typically formulated as a continuous NLP problem where the aforementioned
nonoverlap condition make its feasible region nonconvex. We approximate these
nonoverlap conditions and the bilinear objective function with piecewise linear
and tailored constructs. In doing so, the resulting formulation becomes a MILP
problem.
WC12
12-Franklin 2, Marriott
Optimization Stochastic III
Contributed Session
Chair: Michael Metel, PhD Student, McMaster University,
1280 Main St. West, Hamilton, ON, L8S4M4, Canada,
Michael Metel
1 - A Bilevel Programming Model: Reduction of Dimension of the
Upper Level Problem
Vyacheslav Kalashnikov, Assist. Prof., Tecnologico de Monterrey
(ITESM), Campus Monterrey, 2501 Av. Eugenio Garza Sada
South, Monterrey, NL, 64849, Mexico,
Nataliya Kalashnykova
Bilevel stochastic programming is often applied to model interaction between a
Natural Gas Shipping Company and a Pipeline Operating Company. The problem
is reduced to an also bilevel model but with linear constraints. However, this
reduction makes the dimension of the upper level problem an unbearable burden
even for the modern PC systems. The aim of this paper is a mathematical
formalization of the reduction of the upper level problem’s dimension without
affecting the optimal solution.
2 - Optimization Problem with a Reference Utility Based Stochastic
Dominance Constraint
Jian Hu, Assistant Professor, University of Michigan- Dearborn,
2340 Engineering Complex, 4901 Evergreen Rd, Dearborn, MI,
48128, United States of America, ,
Gevorg Stepanyan
We address a novel approach to relax the second order stochastic dominance,
which characterizes a norm-based functional perturbation region based on a
reference utility function recommended by the decision maker. This approach
best represents the decision maker’s individual preference. We discuss an
optimization problem using this dominance constraint, and provide a solution
method using Bernstein polynomial approximation.
3 - Hybrid Robust-stochastic Optimization Approach for
Closed-loop Supply Chain Network Design
Esmaeil Keyvanshokooh, PhD Student, University of Michigan,
1205 Beal Ave., Ann Arbor, MI 48109-2117, Ann Arbor, MI,
United States of America, , Elnaz Kabir,
Sarah Ryan
Our contribution is to develop a novel hybrid robust-stochastic programming
approach to simultaneously model two different types of uncertainties by
including stochastic scenarios for transportation costs and polyhedral uncertainty
sets for demands and returns. An accelerated stochastic Benders decomposition is
proposed for solving this model. Numerical studies are performed to show the
benefits of our approach.
WC11