2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Heuristics For The Covering Capacitated Vehicle Routing Problem
Christopher John Wishon, Arizona State University, Tempe, AZ,
United States, , Guilherme Sproesser Ferreira,
J. Rene Villalobos
The covering VRP is a variant of the traditional VRP in which a vehicle can satisfy
a customer’s demand by visiting one out of a set of predetermined alternate
locations within the network. This variant is motivated by many practical
applications including the routing of mobile retailers, urban bus lines, and
emergency vehicles. In this work, the Greedy, Sweep, Savings, and Ant Colony
Heuristics are adapted to solve the covering VRP. These techniques are employed
to solve nearly 200 test instances and the results are compared to any known
optimal solutions. These results demonstrate the superiority of the Ant Colony
and Savings methods.
3 - New Formulations For The Hub Interdiction Median Problem
Prasanna Ramamoorthy, IIM Ahmedabad, Vastrapur, Ahmedabad,
380015, India,
In this work, we present new formulations for the hub interdiction median
problem. We present a bi-level formulation and explore reducing it to a single
level using KKT(Karush - Kuhn - Tucker) conditions and closest assignment
constraints. We present new closest assignment constraints for the problem in
addition to the existing ones in literature (Lei 2013). The new closest assignment
constraints has some interesting properties which aids in solving the problem
efficiently. We also present computational results highlighting the efficiency of the
closest assignment constraints and the proposed model in solving the problem.
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Broadway E- Omni
Retail Mgt I
Contributed Session
Chair: Kamal Lamsal, Assistant Professor, Emporia State University,
Campus Box 4039, 1 Kellogg Circle, Emporia, KS, 66801, United States,
1 - Efficient Workforce Scheduling In Retail Stores Considering
Overtime Or Part-time Workforce
Peeyush Pandey, Doctoral Student, Indian Institute of
Management, Indore, IIM Indore, Indore, 453331, India,
Hasmukh Gajjar, Bhavin J. Shah
This paper deals with the problem of identifying optimal workforce size and their
schedule to satisfy hourly and daily requirements of workers at the retail store.
We consider a multiple day planning horizon divided into periods of equal length
for the retail store that caters to daily requirement of customer and offers a wide
variety of product. An optimization model is proposed for both overtime and part-
time workers considering different shift lengths and different lunch and tea
breaks during the working shift. A heuristic presented in the paper guarantees to
obtain optimal number of workers and their schedule.
2 - Analyzing Impact Of Cardinality And Similarity Context-effects On
Assortment Optimization
Uzma Mushtaque, Rensselaer Polytechnic Institute, 110 8th St,
Troy, NY, 12180, United States, , Jennifer Pazour
Assortment planning problem in an online retail environment explicitly modeling
no-choice behavior is presented. Difficulty of selecting an item under cardinality-
context effects and the attraction due to underlying utility are modeled as the
fundamental driver’s behind opting for no-choice. Optimality conditions are
developed for cardinality context effects and for an interaction of cardinality with
similarity effects. Three different algorithms exploit the structure of the optimal
solution under these two conditions.
3 - Assortment Planning And Replacement Under Attractiveness
Decay Effect
Huiqiang Mao, City University of Hong Kong, Tat Chee Avenue,
Kowloon, Hong Kong, 000, Hong Kong, ,
Yanzhi Li
Inspired by assortment renewal strategies of many industries, we consider the
capacitated assortment planning and replacement problem, where the
attractiveness of the product decays over time. Based on Locational Choice
Model, we characterize the structural properties of the optimal assortment. We
also consider the assortment replacement problem, where the retailer is allowed
to update the assortment over the horizon. We explore conditions under which
the retailer should employ this replacement strategy.
4 - The Phantom Inventory Menace: The Effect Of Unobserved
Stock-outs On Lost Sales
Fredrik Eng-Larsson, Postdoctoral Associate, MIT Center for
Transportation and Logistics, Boston, MA, United States,
Daniel Waymouth Steeneck
Based on retail audit data, we find retail inventory records are an unreliable
indicator of out-of-stock (OOS) events. Worse yet, the records are rarely validated
or corrected. As a result, many OOS event are never observed in the inventory
record. We estimate the impact of the unobserved OOS events on lost sales via a
novel demand estimation technique, which accounts for inventory uncertainty in
the presence of scarce inventory record validation.
5 - Warehousing And Shipping Decisions For An Online Replacement
Parts Retailer
Kamal Lamsal, Assistant Professor, Emporia State University,
Campus Box 4039, 1 Kellogg Circle, Emporia, KS, 66801,
United States, Amit Kumar Verma
Online replacement parts sellers offer big selection of products. These products are
held in several locations. With every incoming order, the seller must decide
whether to split the various items from one order or not and from where each
item will ship. We work with an online OEM parts retailer which competes on
customer service level. The retailer charges a flat shipping fee per product and
promises a delivery time. We develop an Approximate Dynamic Programming
(ADP) based algorithm that makes shipping decisions by minimizing the on hand
shipping cost plus estimate of future shipping costs. We use the lessons from the
exercise to decide which parts should be located in which warehouse.
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Broadway G- Omni
Multicriteria Decision I
Contributed Session
Chair: Yuji Sato, Professor, Chukyo University,
101 Yagotohonmach, Showa, Nagoya, Aichi, 466-8666, Japan,
1 - Financial Decision-maker’s Preferences Modeling Within Goal
Programming Model
Belaid Aouni, Associate Dean, Qatar University, College of
Business and Economics, Al Jamiaa Street, Doha, 2713, Qatar,
Goal Programming (GP) model has been applied to financial portfolio selection
problem where several conflicting and incommensurable attributes are
simultaneously aggregated, such as return, risk and liquidity . The aggregation of
the conflicting attributes requires some compromises from the Financial Decision-
Maker (FDM) based on his/her preferences. The aim of this paper is to present a
new typology of the FDM’s preferences modeling within the GP model for
financial portfolio selection.
2 - Rethinking Sfpark’S Demand Response Pricing
Tayo Fabusuyi, Research Associate, University of Michigan, 5520
Baywood Street, Floor #3, Ann Arbor, MI, 15206, United States,
Robert Hampshire
In an effort to eliminate circling and reduce parking search time and cruising,
SFpark, an innovative demand-responsive pricing program was implemented by
the City of San Francisco. Over a two year period, the program was piloted across
seven San Francisco neighborhoods made up of 256 distinct parking blocks. The
evaluation of the pilot program has however met with mixed reviews particularly
with regards to the relationship between price changes and occupancy levels.
These issues are addressed by employing a non-dominated sorting genetic
algorithm approach from which figures of merit are generated that allow for an
objective comparison between treatment and control blocks.
3 - Assets And Liabilities Management Within An Integral Risk
Framework For A Microfinance Institution
Tayo Fabusuyi, Numeritics, Pittsburgh, PA, Contact:
While the microfinance industry has recorded some success in providing financial
services to the poor, it has also attracted criticism with regards to the quality of
services offered and the lack of a robust risk framework observed across the
industry. Using data over a period of a decade (2006-2016), our study addresses
these concerns by employing a multiple-criteria decision analysis which provides
management with a menu of measures of risk-return tuples that maintains fideli-
ty to the bank’s non-financial constraints. The approach is enumerated using
Grameen Bank as a case study.
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