Informs 2015

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INFORMS Philadelphia – 2015
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2 - Distributionally Robust Stochastic Optimization using
Divergences- A Data Driven Strategy
Anand Vidyashankar, Associate Professor, George Mason
University, Department of Statistics, Volgeneau School of
Engineering, Fairfax, VA, 22030, United States of America,
, Jie Xu
We propose a new paradigm for data-driven distributionally robust stochastic
optimization (DRSO). This paradigm integrates existing approaches to decision
making under uncertainty with robust and efficient statistical procedures.
Specifically, it extends the scope of DRSO by centering the ambiguity sets on
density estimates neighborhoods in the space of probability densities. The
proposed approaches are transparent, theoretically justified, and accessible to
researchers and decision makers.
3 - Some Statistical Perspectives on Optimization under
Parameter Uncertainty
Henry Lam, Assistant Professor, University of Michigan, 1205
Beal Ave., Ann Arbor, MI, 48109, United States of America,
Jeff Hong
We consider approaches to improve the quality of solutions for optimizations
under parameter uncertainty, in the case of limited data. We analyze two
computationally tractable methods: bootstrap aggregation, or bagging, and Bayes
estimator in the decision-theoretic framework. Both are simulation-based
schemes that aim to improve the distributional behavior of the optimality gap by
reducing its frequency of hitting large values.
4 - Simulation Optimization When Facing Input Uncertainty
Enlu Zhou, Assistant Professor, Georgia Institute of Technology,
755 Ferst Drive, NW, Atlanta, GA, United States of America,
Xie Wei
This talk makes an attempt at the question of what is a good formulation for
simulation optimization when there is input uncertainty. We propose a risk
formulation of simulation optimization that tries to balance the trade-off between
optimizing under the estimated input model and hedging against the risk brought
by input uncertainty.
MB77
77-Room 300, CC
Supply Chain Management VI
Contributed Session
Chair: Bisheng Du, Assistant Professor, Ningbo University,
818 Fenghua Road, Ningbo, China,
1 - Supplier Development Investments under Competition
Tarun Jain, IIM Bangalore, FPM Office, IIM Bangalore,
Banerghatta R, Bangalore, India, ,
Jishnu Hazra
We model a case, where a buyer is evaluating a new supplier. The buyer allocates
some capacity to the incumbent supplier and makes supplier development
investments in the entrant supplier. Both incumbent and entrant supplier also
exerts improvement investments. We find the optimal investments strategy of
these players and the optimal capacity allocation strategy of the buyer.
2 - Analysis and Design of Retail Backrooms and its Impact on
Supply Chain
Lita Das, Student, MIT, 77 Massachusetts Avenue, E40-286,
Cambridge, MA, 02139, United States of America,
, Edgar Blanco
Backroom space management and supply chain operations are closely linked. We
propose a model to optimally manage backroom space and demonstrate the
impact on retail supply chain planning and design.
3 - An Evaluation of the Progressive Formulation (PF) through the
Modeling of the PCSA
Daniel Mota, Researcher, MIT, Rua Jose de Magalhaes 373, Vila
Clementino, Sao Paulo, SP, 04026, Brazil,
Roberto Perez-franco
Progressive Formulation (PF), an ad-hoc approach recently proposed for
formulating a supply chain strategy, has shown potential in applied projects but
has never been objectively evaluated. This paper attempts a first evaluation of the
merits of the PF approach, by modeling PF as a greedy algorithm and comparing
its results against an optimal solution for the same data set. Results are compared
in terms of the quality of the solution generated and the amount of information
needed to achieve it.
4 - Capacity Planning over a Finite Time Horizon with Dual Contracts:
An Optimization Approach
Ramya Ravi, Student, Indian Institute of Technology, Madras,
Chennai, 600036, India, ,
Haritha Thirrumalai, Rajendran Chandrasekharan,
Vivekanandan Srinivasan
We consider a supply chain with multiple products manufactured using processes
outsourced to suppliers by the manufacturer. Capacity planning contracts
(i.e.,fixed charge and option, with setup/order costs) are considered. We present
an algorithm to determine the capacity investments, considering the total supply
chain profit over a finite time horizon.
5 - Optimal Fulfillment Decisions in a Capacitated Online Retailing
System with Different Leadtimes
Bisheng Du, Assistant Professor, Ningbo University,
818 Fenghua Road, Ningbo, China,
Online retailers offer more options, like flexible delivery, pricing, etc. We consider
an inventory system where customers may have different lead-times under the
retailer’s capacity. The retailer has a primary warehouse and many regional
warehouses. The regional warehouses fulfill the customers’ orders by on-hand
inventory, or the primary warehouse will fulfill orders with longer time. Our
intension is to analyze the performance of the capacitated retailing system under
the multistage setting.
MB78
78-Room 301, CC
Shipping and Transportation for Supply Chains
Contributed Session
Chair: Sherif Masoud, Operations Research Analyst, RockTenn, 3950
Shackleford Rd., Duluth, United States of America,
1 - Port Logistics and the Voice of the Customer
Richard Monroe, Visiting Assoc Prof, Longwood Univ, College of
Business and Econ, 201 High Street, Farmville, VA, 23120,
United States of America,
Customers are key stakeholders for logistics services through the various modes
which include seaports, trucking, rail and inland ports. Primary customers such as
manufacturers and retailers are highly dependent on the smooth flow of freight
through the logistics system. Customer expectations for logistics services have
received limited attention in previous research. This paper will utilize a
combination of approaches to explore the voice of the customer in the port
logistics setting.
2 - A New Formulation for the Cyclic Inventory Routing Problem and
the Solution Method
Zhe Liang, Professor, Tongji University, No. 1239, Siping Road,
Shanghai, 200092, China,
W. Art Chaovalitwongse
We study a cyclic inventory routing problem (IRP). The traditional exact methods
for IRP use an arc-based model, in which a variable represents a possible vehicle
flow between a pair of customers. We develop a Dantzig-Wolfe reformulation for
the arc-based model. To solve the problem efficiently, we develop a set of valid
inequalities and a column generation algorithm. Computational results show that
the new model can obtain near optimal solutions to very large test cases in a
reasonable time.
3 - Robust Supply Chain System under Yield Uncertainty
Samir Alsobhi, PhD Candidate, Wichita State University, 11328 E
Pine Meadow Ct, Wichita, KS, 67206, United States of America,
, Krishna Krishnan
Products are often damaged in transit.These damages are stochastic in
minimize the impact of damage,the selection of routes should consider not only
the expected damage but also the variability of this research,the first
model is of the supply chain network in order to minimize total cost,which
consists of product cost and transportation cost while considering multiple routes
and the second model,the concept of robust design has been applied
to minimize damage.
4 - A Floating Price Contract for the Ocean Freight Industry
Ruina Yang, Xi’an Jiaotong University, No. 28 West Xianning
Road, Xi’an, China,
We propose a floating price policy to address the shipper default issue. Specifically,
the shipper has to make a tradeoff between not fulfilling all committed capacity to
secure a lower spot price in the low season and purchasing the capacity at a
higher floated price in the high season. The results reveal that the non-capacity
commitment contract serves both parties’ best interests under a tight-capacity
market, while the floating price contract is the most effective in an over-capacity
market.
MB77