Technical Sessions – Monday July 11

Delivering superior service to retain customers is critical to a firm’s sustainability.
As it is difficult for firms to avoid all service failures (SFs), the service
recovery (SR) implementation has then become an important issue. In view of
QFD is useful for ensuring customer’s voice being deployed throughout all the
planning/designing stages, the aim of this study is to develop a SR model by
adopting QFD as the basis. The proposed SR model is illustrated using data
collected from Taiwan’s Mobile-Telecom industry. Results show that QFD is
useful for identifying the core resource for SR.
3 - A Study on Constructing Green Consumption Behavior
System by DEMATEL Method
Shu-Ping Lin, Technology Management, Chung Hua University,
707, Sec.2, WuFu Rd., 30012, Hsinchu, Taiwan,
splin@chu.edu.tw, Yahui Chan, Chen Ping-Hsien
As the green demands have continuously increased, to understand the antecedents
of consumer’s acceptance intention towards green products will be
helpful for green marketing. In view of the relevant studies discussing green
consumption behavior (GCB) are lack, the aim of this study is to build a GCB
system by DEMTEL method in order to clarify the interrelationship between
the antecedents from different theories. Solar industry in Taiwan is chosen and
seven experts were interviewed. All the results will be expected to give as the
reference for green marketing.
4 - Bridge the Gaps: Examining Restaurant Service Quality
from the Perspectives of Customers, Management
and Employees
Chien-Lin Lin, Department of Technology Management, Chung
Hua University, Department of Tourism Management, Hsing Wu
College, N0. 707 Sec. 2 Wufu Rd., 30012, Hsinchu, ROC,
Taiwan, 082001@mail.hwc.edu.tw, Ming Chun Tsai
From the services triangle perspective, the interlinked groups, meaning customers,
management and providers, are integral for quality service delivery.
Few studies have investigated on the gaps between the three. In this study an international
tourist hotel in Taiwan was chosen to empirically examine the gaps
between customers’ service expectations and service received, and the gaps
between customers’ service expectations and the perceptions of these expectations
by the management and employees. A revised importance-performance
analysis was then used to construct a service evaluation matrix to identify areas
for improvement in the hope of giving some insight for the hospitality industry.
� MB-06
Monday, 14:00-15:30
Meeting Room 105
Aviation Optimization
Stream: Transportation
Invited session
Chair: Vikrant Vaze, Civil and Environmental Engineering, MIT, 77,
Massachusetts Avenue, 02139, Cambridge, MA, United States,
vikrantv@MIT.EDU
1 - Multi-agent Models of Airline Competition for Congestion
Mitigation in the National Air Transportation System
Vikrant Vaze, Civil and Environmental Engineering, MIT, 77,
Massachusetts Avenue, 02139, Cambridge, MA, United States,
vikrantv@MIT.EDU, Cynthia Barnhart
Delays to flights and passengers cost billions of dollars annually. Airline competition
is closely related to and partially responsible for exacerbating the congestion
situation. First, we develop bounds on the degree of inefficiency introduced
by airline competition. Next, we present models of airline competition
and efficient algorithms for Nash equilibrium computation. Finally, we evaluate
the performance of simple demand management strategies in a competitive
environment. Results establish the connection between competition and congestion,
and show that significant improvements in flight and passenger delays
and in airline profits can be achieved through simple slot reduction strategies.
2 - Stochastic Integer Programming Models for Air Traffic
Flow Management Problems
Michael Ball, R H Smith School of Business, University of
Maryland, 20742, College Park, MD, United States,
mball@rhsmith.umd.edu
IFORS 2011 - Melbourne MB-07
In this paper we address a stochastic air traffic flow management problem that
arises when airspace congestion is predicted, so that the number of flights passing
through a volume of airspace must be reduced. We formulate a stochastic
integer program that assigns to each flight either a delayed departure time or
the decision to use a secondary route. These decisions take into account a
distribution of possible weather scenarios. We conduct experiments that both
demonstrate the computational efficiency of our approach and draw conclusions
regarding appropriate flow management strategies.
3 - Improving Schedule Robustness with Flight Re-timing
and Aircraft Swapping
Sophie Dickson, Department of Mathematics and Statistics, The
University of Melbourne, 3010, Parkville, VIC, Australia,
sophiedickson@gmail.com, Natashia Boland
All plans go astray, especially airline schedules. Flight delays have knockon
effects that frustrate passengers and cost airlines money. Most schedules
include slack time to reduce knock-on delays. We present new models that
re-time and swap flights between aircraft in a schedule, redistributing slack to
minimise knock-on effects. We extend previous research by combining flight
retiming and aircraft routing in one model. Our models optimise the delay distribution,
rather than average or total delay measures. We cover the model, how
parameters are set from real data, and experimental results.
4 - An Optimisation-based Approach to Airline Disruption
Recovery
David Ryan, Engineering Science, The University of Auckland,
Private Bag 92019, 1, Auckland, New Zealand,
d.ryan@auckland.ac.nz
A disruption event in airline operations affects planned schedules for aircraft,
crew and passenger resources. In this talk I will describe a solution framework
which attempts to minimize the extent of disruption to the original planned
schedules. The solution framework involves a restricted disruption neighbourhood
of disrupted resources. Within the neighbourhood a set partitioning
model is formulated to reschedule affected resources while ensuring continuous
boundary conditions exist for all resources within the neighbourhood to
their undisturbed schedules outside the neighbourhood.
� MB-07
Monday, 14:00-15:30
Meeting Room 106
Cutting and Packing 2
Stream: Cutting and Packing
Invited session
Chair: Karen Daniels, Department of Computer Science, University
of Massachusetts Lowell, One University Avenue, Olsen Hall, Room
216, MA 01854, Lowell, United States, kdaniels@cs.uml.edu
1 - A Genetic Algorithm No-Fit Polygon Placement Technique
for Improving Build Volume Utilization of Layer
Manufacturing Machines’
Vassilis Dedoussis, Industrial Management & Technology,
University of Piraeus, 80 Karaoli & Dimitriou str., 185 34,
Piraeus, Greece, vdedo@unipi.gr, Vassilis Canellidis, John
Giannatsis
Rapid Manufacturing (RM) is an emerging set of technologies aiming at manufacturing
end-use products using Layer Manufacturing (LM) technologies. The
present work examines the application of a Genetic Algorithm in conjunction
with an effective placement rule based on the notion of No Fit Polygon, as a
mean of optimizing RM processes, i.e. the build volume of LM technologies,
that due to technical or quality reasons prohibit the fabrication of a part on top
of another. The performance of the proposed technique is demonstrated via a
case study concerning representative "real world’ parts.
2 - Regarding an Alternative Method for Translational
Single-Item Containment
Jason M’Sadoques, University of Massachusetts Lowell, 01854,
Lowell, United States, jlyonm@gmail.com, Karen Daniels
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