Technical Sessions – Monday July 11

MB-12 IFORS 2011 - Melbourne
4 - Light-Tailed Asymptotics of the Joint Queue Length
Distribution of a Multiclass M/G/1 Queue with the FCFS
Service Discipline
Kenzo Hara, Dept. of Systems Science, Graduate School of
Informatics, Kyoto University, 606-8501, Kyoto, Japan,
ken3@sys.i.kyoto-u.ac.jp, Hiroyuki Masuyama, Yutaka
Takahashi
This talk is concerned with a multiclass M/G/1 queue with the FCFS service
discipline, which is fed by independent Poisson arrival processes with different
service time distributions. For the multiclass M/G/1 queue, it is, in general,
difficult to obtain an explicit expression of the stationary joint queue length distribution.
We derive a light-tailed asymptotic formula for the stationary joint
queue length distribution, assuming that the service time distributions are all
light-tailed. The asymptotic formula is useful to understand the tail behavior
and expected to serve as an approximation.
� MB-12
Monday, 14:00-15:30
Meeting Room 205
Services Management
Stream: Contributed Talks
Contributed session
Chair: Ronsen Purba, Information Technology, STMIK Mikroskil,
Jalan Thamrin No.124/140 Medan, Jalan Sembada XI No. 9, 20212,
Medan, North Sumatera, Indonesia, ronsen@mikroskil.ac.id
1 - A Case Study of Design and Implement of a Service
Business on a Heavy Machinery Manufacturing Firm
Nobuhiko Nishimura, Faculty of Economics, Nagasaki
University, 4-2-1, Katafuchi, 850-8506, Nagasaki, Japan,
nishimra@nagasaki-u.ac.jp
Three major perspectives relating to service business are reviewed, followed by
an in-depth case study on a new e-service business design and implementation
initiative at a heavy machinery manufacturing firm. It is confirmed that profitable
services business can be designed based on strategic fitting to capability
and position already built by the firm in its conventional business, with repeat
prototyping to elicit potential customers’ requirements. The resulting system
makes the service offering complementary to and dependent upon products to
raise the entry barrier against competitors.
2 - Verification of e-customer Purchasing Behavior Pattern
Model by Cohort Analysis
Hisaya Sunada, Web Business Technology, The Kyoto College of
Graduate Studies for Informatics, Japan,
hisaya.sunada@gmail.com, Tong Wu, Wang Chao, Maotao
Chen, Hongxue Wang, Hong Seung Ko
In the e-business environment, the visualization of e-customer purchasing behavior
is absolutely necessary to select the most valuable e-customer who must
be retained. In this paper, we perform the cohort analysis to the segmentation
factor, that is purchasing frequency ,profitable sales and 7 Steps of e-customer
purchasing behavior process in the e-customer purchasing behavior pattern
model which is proposed by Ko et al. Consequently, we check up the validity
of the e-customer purchasing behavior pattern model by the characteristics
on the e-customer purchasing behavior pattern as a result.
3 - A use of Bootstrapped Malmquist Indices to Assess
Productivity Changes of the Iranian Banks
16
Amir Arjomandi, Economics, University of Wollongong, 5/20,
Smith Street, 2522, Wollongong, NSW, Australia,
amira@uow.edu.au, Abbas Valadkhani
This study employs various bootstrapped Malmquist indices and efficiency
scores to investigate the effects of government regulation on the performance of
the Iranian banking industry over the period 2003-2008. An alternative decomposition
of the Malmquist index, introduced by Simar and Wilson (1998a), is
also applied to decompose technical changes further into pure technical change
and changes in scale efficiency. A combination of these approaches facilitates
a robust and comprehensive analysis of Iranian banking industry performance.
While this approach is more appropriate than the traditional Malmquist approach,
for the case of banking efficiency studies, it has not previously been
conducted for any developing country’s banking system. The results obtained
show that although, in general, the regulatory changes had different effects on
individual banks, the efficiency and productivity of the overall industry declined
after regulation. We also find that productivity had positive growth before
regulation mainly due to improvements in pure technology, and that government
ownership had an adverse impact on the efficiency level of state-owned
banks. The bootstrap approach demonstrates that the majority of estimates obtained
in this study are statistically significant.
4 - On Deciding Sustainable Distribution Centre of a Supply
Chain
Ronsen Purba, Mathematics Dept., STMIK Mikroskil
Medan/Graduate School of Mathematics, University of Sumatera
Utara, Jalan Thamrin No. 140 Medan North Sumatera, Medan,
Indonesia, purbaronsen17@yahoo.com
A supply chain is a network that performs the procurement of raw material, the
transportation of raw material to intermediate and end products, and the distribution
of end products to retailers or customers. In this paper we address a new
approach for solving a supply chain optimization model to decide distribution
centres based on environmental consideration.
� MB-13
Monday, 14:00-15:30
Meeting Room 206
Data Mining and Continuous Optimization
Stream: Continuous and Non-Smooth Optimization
Invited session
Chair: Zeev (Vladimir) Volkovich, Ort Braude Academic College,
Yehiam 6, 21823, Karmiel, Israel, zeev@actcom.co.il
1 - Necessary Conditions for the Confidence Level of the
Randomized Cluster Stability Algorithm
Oleg Granichin, Mathematics & Mechanics, Sankt-Petersburg
State University, 28 Universitetskii prospect, Petergof, 198504,
St. Petersburg, Russian Federation, Oleg_granichin@mail.ru,
Renata Avros, Zeev (Vladimir) Volkovich, Mikhail Morozkov
The well known machine learning problem is an estimation of clusters amount
in a given dataset. We offer the approach in the framework of the common
"elbow" methodology such that the true number of clusters is recognized as the
discontinuity point of the differential risk function. We apply a randomized algorithm
to allocate this position. The scenario approach is used to significantly
reduction the computation complexity. We present necessary conditions to provide
the chosen by user level of confidence. Numerical simulation example of
an unknown huge amount of clusters illustrates the theory.
2 - Cluster Analysis of A Tobacco Control Data Set
Zari Dzalilov, School of Information Technology and
Mathematical Sciences, University of Ballarat, 1, University
Drive, 3353, Ballarat, VIC, Australia,
z.dzalilov@ballarat.edu.au, Adil Bagirov
Development of theoretical and methodological frameworks in data analysis
is fundamental for modeling complex tobacco control systems. Optimization
methods can detect nonlinearity and be effective analysis tools of complex data.
We evaluate the modified global k-means clustering algorithm for a massive set.
Cluster analysis identified fixed and stable clusters in the studied data. Clusters
correspond to smoker groups with similar behavior, identification of these clusters
may allow modification of existing tobacco control systems and on design
of future data acquisition surveys.
3 - Algorithm Learning Based Neural Network for Multivariate
Classification
Hyunsoo Yoon, School of Industrial Management Engineering,
Korea University, Anam 5-ga, Anam-dong, Sungbuk-gu,