Technical Sessions – Monday July 11

� TD-11
Tuesday, 17:00-18:30
Meeting Room 112
Simulation for Supply Chain Management
Stream: Simulation - Sponsored by I-SIM
Invited session
Chair: Preston White, Systems and Information Engineering,
University of Virginia, P.O. Box 400747, 151 Engineers’ Way,
22904-4747, Charlottesville, VA, United States,
kpwhite@virginia.edu
1 - Modelling and Simulation of a Palm Oil Mill towards Effective
Supply Chain Management
Fazeeda Mohamad, Technology Management, Universiti
Malaysia Pahang, H-95 Jalan Karyawan 11, Taman Guru, 25150,
Kuantan, Pahang, Malaysia, adeezaf@yahoo.com
This paper evaluated the capacity of the palm oil mill. The under utilized of
capacity effect the capacity of the mill due to shortage of materials. Data were
collected from a palm oil mill as our case study. Modelling and simulation
were used in designing and accessing the mill operation using Arena simulation.The
result will help the management to do better capacity planning towards
effective supply chain.
2 - Time Depending Network Node Modelling and Effectcause
Vehicle Modelling for Sustainable Public Transportation
Systems
Joeri Van Mierlo, MOBI, Vrije Universiteit Brussel, Pleinlaan 2,
1050, Brussels, Belgium, jvmierlo@vub.ac.be
This article describes a multi-train mathematical model for rail networks capable
of estimating the energy consumption of different tram and metro networks.
The simulations determine the vehicles and substations power and the
energy exchange among simultaneously running vehicles. Energy consumption
reduction that can be achieved by introducing energy storage technologies
in sustainable transportation systems is evaluated
3 - Empirical Tests of Variables Acceptance Sampling
Plans
Preston White, Systems and Information Engineering, University
of Virginia, P.O. Box 400747, 151 Engineers’ Way, 22904-4747,
Charlottesville, VA, United States, kpwhite@virginia.edu
Acceptance sampling, originally developed as an approach to determining the
quality of procured items, can be adapted to verifying design requirements using
Monte Carlo methods (White, et al., 2009). Extending this research, we
implemented variables acceptance sampling plans for six standard output distributions
reported in the literature. In this paper, we present the results of tests
which provide an independent assessment of the validity and accuracy of these
plans.
� TD-12
Tuesday, 17:00-18:30
Meeting Room 205
Networks
Stream: Contributed Talks
Contributed session
Chair: Shunji Umetani, Osaka University, 2-1 Yamadaoka, Suita,
560-0871, Osaka, Japan, umetani@se.uec.ac.jp
1 - A Model of Adding Relation between the Top and a
Member in a Linking Pin Organization Structure
Kiyoshi Sawada, Department of Information and Management
Science, University of Marketing and Distribution Sciences, 3-1,
Gakuen-nishi-machi, Nishi-ku, 651-2188, Kobe, Japan,
Kiyoshi_Sawada@red.umds.ac.jp
IFORS 2011 - Melbourne TD-13
The purpose of our study is to obtain an optimal set of additional relations to
the linking pin organization such that the communication of information between
every member becomes the most efficient. This study proposes a model
of adding relation between the top and a member in a linking pin organization
where every pair of siblings in a complete K-ary tree of height H is adjacent.
When a new edge between the root and a node with a depth N is added, an
optimal depth N* is obtained by minimizing the total distance which is the sum
of lengths of shortest paths between every pair of all nodes.
2 - Conjecture of Aouchiche and Hansen about the Randic
Index
Ljiljana Pavlovic, Department of Mathematics, Faculty of
Natural Sciences nd Mathematics, Radoja Domanovica 14,
34000, Kragujevac, Serbia, pavlovic@kg.ac.rs, Marina
Stojanovic
Let G(k,n) be the set of connected simple graphs which have n vertices and the
minimum degree of vertices is k. The Randic index of a graph G is defined as
sum of d(u)d(v) raised to the power of -1/2 , where d(u) is the degree of vertex
u and the summation extends over all edges uv of G. We prove the conjecture
given by Aouchiche and Hansen on the graphs for which the Randic index attains
its minimum value when k is greater or equal to n/2. We show that the
extremal graphs have only degree k and degree n-1, and the number of vertices
of degree k is as close to n/2 as possible.
3 - Shortest Path Approach to Find Critical Path in a Network
Model.
Shruthi S Kumar, Telecommunication, PES Institute of
Technology, 100 Ft Ring Road BSK III Stage, 560085,
Bangalore, Karnataka, India, shruthulisha@gmail.com,
Guruprasad Nagaraj
Networks provide a natural way of graphically displaying the flow of activities
in a major project. The critical path of a project network is the longest path
and the main purpose is to identify those activities whose crashing may reduce
the overall duration of the project. Dijkstra’s algorithm solves the shortest path
problem on a weighted directed graph. In this paper, we have made an attempt
to find out how the shortest path algorithm can be slightly modified to find the
critical path of a network. We have compared this approach with the regular
method and found to be more efficient.
4 - Two-probe Routing Model and Algorithm for Multi-chip
Module Substrates
Shunji Umetani, Osaka University, Japan,
umetani@ist.osaka-u.ac.jp, Keisuke Murakami, Hiroshi Morita
The testing faults on multi-chip module (MCM) substrates is essential but quite
time consuming task in assembling circuit boards. We formulate the problem
of routing a pair of testing probes on MCM substrates as a constrained shortest
path problem, and propose an exact algorithm and an approximate algorithm
using labeling method.
� TD-13
Tuesday, 17:00-18:30
Meeting Room 206
Optimization, Forecasting, Renewable
Energy and Electricity Grid II
Stream: Continuous and Non-Smooth Optimization
Invited session
Chair: Asef Nazari, School of Mathematics and Statistics, University
of South Australia, OC Building, Mawson Lakes Campus, 5095,
Mawson Lakes, South Australia, Australia, asef.nazari@unisa.edu.au
Chair: Jerzy Filar, Mathematics and Statistics, University of South
Australia, Mawson Lakes Blvd, 5095, Mawson Lakes, SA, Australia,
j.filar@unisa.edu.au
Chair: Manju Agrawal, Mathematics and Statistics, University of
South Australia, School of Mathematics and Statistics, Mawson
Lakes, 5095, Adelaide, South Australia, Australia,
manju.agrawal@unisa.edu.au
1 - Optimal Transmission Expansion Planning for Increasing
Wind Power Penetration
Asef Nazari, School of Mathematics and Statistics, University of
South Australia, OC Building, Mawson Lakes Campus, 5095,
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