Technical Sessions – Monday July 11

Mathematical models are used to explain why manufacturing systems evolved
as they did over the last 300 years. I begin with the motives for the factory
system, then move to the introduction of flow lines, the survival of batch production
systems, the advent of moving belt assembly lines, transfer lines, group
technology, flexible manufacturing systems and the Toyota sewing system. The
talk will show how system improvement arose from an understanding of both
variability and its sources and the characteristics of workers and machines.
Some current challenges will be discussed.
� TB-05
Tuesday, 11:00-12:30
Meeting Room 104
Marketing/Operations II
Stream: OR and Marketing
Invited session
Chair: Rick So, UC Irvine, 92697, Irvine, CA, United States,
rso@uci.edu
Chair: Kumar Rajaram, UCLA Anderson School, 100 Westwood
Plaza, 90095, Los Angeles, CA, United States,
krajaram@anderson.ucla.edu
1 - Distribution Planning to Optimize Profits in the Motion
Picture Industry
Kumar Rajaram, UCLA Anderson School, 100 Westwood Plaza,
90095, Los Angeles, CA, United States,
krajaram@anderson.ucla.edu
We consider the distribution planning problem in the motion picture industry.
This problem involves forecasting theater-level box office revenues for a given
movie and using these forecasts to choose the best locations to screen a movie.
We develop and test our methods on realistic box office data and show that it
has the potential to significantly improve the distributor’s profits. We also develop
some insights into why our methods outperform existing practice, which
are crucial to their successful practical implementation.
2 - Supply Chain Models with Preferred Retailer Privy to
Supplier’s Inventory Information
Hamed Mamani, Dept of Information Systems and Operations
Management, University of Washington, Foster School of
Business, 98195, Seattle, WA, United States,
hmamani@u.washington.edu, Kamran Moinzadeh, Apurva Jain
In a supply chain consisting of a supplier and several retailers, some of the
retailers have preferred status, providing them with information about the supplier’s
inventory level. Such status can be due to strategic behavior of retailers
and learning the supplier’s replenishment policy. Preferred retailers, thus, can
be proactive and inflate their orders when supply gets short. We study the dynamics
of such supply chains as a Stackelberg game where retailers react after
the supplier has fixed his strategy. We evaluate outcome of the resulting game
with solution of the centralized problem.
3 - The Planning of Guaranteed Targeted Display Advertising
John Turner, Paul Merage School of Business, UC-Irvine, 92697,
Irvine, CA, United States, john.turner@uci.edu
Ad networks increasingly strive to apply planning models to broad classes of
targeted display advertising, including banner ads, in-game advertising, and
digital TV ads. We formulate a broadly-applicable ad planning problem as a
quadratic transportation problem, and show that the quadratic objective is a
good surrogate for several important performance metrics. Moreover, we exploit
the quadratic objective and develop two complimentary algorithms which
intelligently aggregate the audience space in a manner that dramatically reduces
problem size while obtaining near-optimal solutions.
4 - Diffusions of Mobile Cellular Phones in Sub Sahara
Africa
Chaiho Kim, OMIS Department, Santa Clara University, 500 El
Camino Read, 95070, Santa Clara, CA, United States,
ckim@scu.edu
It is widely believed that mobile phones will play critically important roles for
economic developments of countries in Sub Sahara Africa. Using statistical
models, this paper will examine how the diffusions of mobile phones in Sub
Sahara Africa are related to economic, cultural, and other variables such as different
geographical regions. The paper will also examine whether the relations
found for the mobile phones are significant different from those found for the
main fixed phone lines.
IFORS 2011 - Melbourne TB-06
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Tuesday, 11:00-12:30
Meeting Room 105
Routing Problems :Innovative Applications
and Solution Techniques
Stream: Transportation
Invited session
Chair: Pierre Dejax, IRCCyN, Ecole des Mines de Nantes, La
Chantrerie, 4, rue Alfred Kastler, BP 20722, 44307, Nantes cedex 3,
France, Pierre.Dejax@emn.fr
1 - The Split Delivery Capacitated Team Orienteering Problem
M. Grazia Speranza, Dept. of Quantitative Methods, University
of Brescia, C.da Santa Chiara, 50, 25122, Brescia, Italy,
speranza@eco.unibs.it, Claudia Archetti, Nicola Bianchessi,
Alain Hertz
We study the capacitated team orienteering problem with split deliveries. Potential
customers are associated with a demand and a profit. The customers to
be served by a fleet of capacitated vehicles have to be identified to maximize
the collected profit, with constraints on the maximum time duration of each
route and the vehicle capacity constraints. We show that the profit collected by
allowing split deliveries may be as large as twice the profit collected without
split deliveries. We present exact and heuristic algorithms and test the proposed
approaches on several sets of instances.
2 - Flexible Buses for Manhattan
Felisa Vazquez-Abad, Computer Science Dept., City University
New York, 695 Park Ave, Room HN1000E, 10065, New York,
United States, felisav@hunter.cuny.edu, Jennie Lioris, Guy
Cohen
Few privately owned cars circulate in Manhattan, yet the traffic congestion has
become a serious problem. People with limited mobility and senior citizens
avoid subways, cannot afford taxis and face excessive delays travelling by bus.
We explore an alternative formulation where cars adjust their routes on demand,
but may take several passengers. Pilot studies in Paris show that this system can
achieve 80% occupation rate, instead of the 60% idle taxis roaming the streets
today. We will present online routing allocation algorithms that use threshold
optimization under different pricing models.
3 - Enhanced Variable Neighborhood Search for Multi- Period
Inventory Routing Problem Model with Time Varying
Demand
Noor Hasnah Moin, Institute of Mathematical Sciences,
University of Malaya, 50603, Kuala Lumpur, Malaysia,
noor_hasnah@um.edu.my
We consider a multi-period Inventory Routing Problem (IRP) that faces time
varying demand of multi-product from the assembly plant, in a many-to-one
distribution network consisting of an assembly plant and many geographically
dispersed suppliers each supplying a distinct product to the plant. The product
is ready for collection when the vehicle arrives and all demand must be met
without backlogging. The inventory holding cost is product specific and a fleet
of capacitated homogeneous vehicles transport products from the suppliers to
meet the demand of the plant in each period. The problem is formulated as a
mixed integer programming problem. We propose a solution method based on
the Variable Neighborhood Search where several heuristics are incorporated at
various stages of the algorithm. The algorithms are run on several problems
from the literature and the results are compared with the Genetic Algorithms.
VNS performs better on larger problems.
4 - Robust Scenario Generation for a Real Large-Scale Inventory
Routing Problem
Pierre Dejax, IRCCyN, Ecole des Mines de Nantes, La
Chantrerie, 4, rue Alfred Kastler, BP 20722, 44307, Nantes
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