Informs 2015

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INFORMS Philadelphia – 2015
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3 - Retail Inventory Optimization for the U.S. Navy
Javier Salmeron, Naval Postgraduate School, Operations Research
Dept., GL-214, Monterey, CA, 93943, United States of America,
, Emily Craparo
We present a mixed-integer linear model to guide retail (site-based demand level)
inventory decisions for the Naval Supply Systems Command (NAVSUP), Weapons
Systems Support. An (s,Q) model optimizes reorder points and order quantities
for thousands of items in order to minimize deviations from target fill rates, with
demand uncertainty, budget and order quantity constraints. We compare branch-
and-bound with Lagrangian relaxation solutions, and our results with those from
other NAVSUP tools.
TC02
02-Room 302, Marriott
Network Applications in Homeland Security
Cluster: Homeland Security
Invited Session
Chair: Thomas Sharkey, Rensselaer Polytechnic Institute, 110 8th
Street, Troy, NY, 12180, United States of America,
1 - Novel Bilevel Programming Approaches for Interdicting
Multi-tiered Illegal Supply Chains
N. Orkun Baycik, Rensselaer Polytechnic Institute, 110 8th Street,
Center for Industrial Innovation, Troy, NY, 12180, United States
of America, , Thomas Sharkey, Chase Rainwater
We study a resource allocation problem faced by law enforcement in arresting
criminals in the drug flow and information flow networks. The objective of law
enforcement is to minimize the maximum amount of drugs reaching end users.
There exist interdependencies between the networks which leads to a network
interdiction problem with a discrete inner problem. We apply a novel dual-based
reformulation technique to solve an equivalent single-level problem and present
computational results.
2 - Bi-level Stochastic Network Interdiction Model for Deployment of
Cyber-security Countermeasures
Apurba Nandi, Mississippi State University, P.O. Box 9542,
Mississippi State University, Mississippi State, MS, 39762,
United States of America, Hugh Medal
We study how best to deploy cyber-security countermeasures to protect a cyber-
network against attacks. We propose a bi-level stochastic network interdiction
model capturing the interaction between the attacker and the defender as a
sequential stackelberg game played on an attack graph. We consider that the
attacker’s knowledge about the topology of the attack graph, and the attacker’s
and the defender’s knowledge about each other’s actions are uncertain. We
develop algorithm to solve the model.
3 - Vitality Measures for Multigraphs with Applications to
Communications Networks
Sarah Nurre, Assistant Professor, Air Force Institute of
Technology, 2950 Hobson Way, WPAFB, OH, 45433, United
States of America, Christopher Hergenreter
We consider the problem of determining the most vital arcs to protect within a
multigraph, such as a communications network. Traditional vitality measures are
insufficient as they often examine single arc failures which have no impact on
multigraphs due to parallel arcs between pairs of nodes. Herein, we propose and
examine set based vitality measures for multigraphs. We perform and present the
results of promisting computational results multi-mode military communications
networks.
4 - Efficient Resilience Optimization of Interdependent Networks
Andres Gonzalez, Rice University, 6100 Main Street, MS-318,
Ryon 203, Houston, TX, 77005, United States of America,
Leonardo Dueñas-osorio,
Andres Medaglia, Mauricio Sánchez-silva
MIP models of the Interdependent Network Design Problem (INDP) have proved
to be effective tools to study and improve the resilience of systems of
interdependent infrastructure networks. Nevertheless, these MIP models have
limited scalability for large realistic systems. In this work, we present an enhanced
methodology to optimize the resilience of interdependent networks, based on the
joint use of decomposition techniques and efficient reformulations of the INDP
models.
TC03
03-Room 303, Marriott
Inventory Management I
Contributed Session
Chair: Jun-yeon Lee, California State University, Northridge, 18111
Nordhoff St, Northridge, CA, 91330-8378, United States of America,
1 - Forecasting of Demand Tail Distribution for Inventory Optimzation
Antony Joseph, Staff Data Scientist, Walmart Labs,
1001 National Avenue, Apt. 107, San Bruno, CA, 94066,
United States of America,
We discuss a novel technique for forecasting demand tail distribution for items in
the Walmart e-commerce inventory. The methodology first estimates the
quantiles of the demand distribution, followed by fitting a parametric distribution
using a suitable metric. The method is seen to be robust to high observed
variability in demand. Performance of the proposed approach is assessed using
Supply Chain metrics such as Weeks of Supply and Met Demand.
2 - Strategic Safety Stocks under Guaranteed Service and
Constrained Service Models
Ton De Kok, TU Eindhoven, Paviljoen E.04, P.O. Box 513,
Eindhoven, Netherlands,
In this presentation we discuss our findings on a set of real-life supply chains
concerning the positioning of safety stocks in the supply chain. We compare the
results from models under the guaranteed service assumption and under the
constrained service assumption. The latter assumption follows the classical Clark
and Scarf model for serial multi-echelon systems. Furthermore, we discuss some
implications of the guaranteed service assumption in case of a bounded demand
formulation.
3 - Scarcity Effect on Dual-channel Supply Chain
Baoshan Liu, PhD Student, Huazhong University of Science and
Technology, School of Management, 1037 Luoyu Road, Wuhan,
China, , Shihua Ma
We consider manufacturer’s dual-channel sale system where customers get the
product the direct channel with limited quantity. The limited quantity of the
direct channel releases a scarcity message that consumers will increase their
purchasing desire. Both the manufacturer and the retailer choose their own
decision variable to maximize their respective profits considering scarcity effect.
We model the problem using Stackelberg games and try to find the best solution
from different perspectives.
4 - An Optimal Inventory Replenishment Considering Product
Life Cycle
Shunichi Ohmori, Assistant Professor, Waseda University, Room
51-15-05, Okubo 3-4-1, Shinjuku, Tokyo, 169-8555, Japan,
Kazuho Yoshimoto
We consider a problem of determining initial and replenishment order quantities
that minimize the cost of lost sales, inventory holding cost, fixed ordering cost,
and obsolete inventory subject to stochastic demands. We model this problem as a
multi-stage problem where the demands and prices of products lie in some
uncertainty set depending on their life cycle. We develop a dynamic programming
method to solve this problem.
5 - Vendor-managed Inventory with a Time-dependent
Stockout Penalty
Jun-yeon Lee, California State University, Northridge, CA,
18111 Nordhoff St, Northridge, CA, 91330-8378,
United States of America,
We examine the problem of designing a vendor-managed inventory (VMI)
contract with a time-dependent stockout penalty in a stochastic (Q, r) inventory
system, in which the supplier is charged a stockout penalty that depends on the
length of the time during which stockouts occur at the customer. The customer
chooses the stockout penalty and offers the VMI contract to the supplier, and the
supplier can accept or reject the contract. We examine the optimal behaviors of
the two parties.
TC02