Simulation Analysis of Inbound Call Center of a
City-gas Company
Soemon Takakuwa (Nagoya University) and Takako
Okada (Matsushita Electric Industrial Co., Ltd.)
Abstract:
An inbound call center of a city-gas company was
simulated to examine the proper target of the service level procedures were
proposed to find the optimal number of agents, considering their skills and
the scheduling of the agents to meet the frequency of customer calls. First,
integer programming was adopted to obtain an initial feasible solution.
Second, a special-purpose system was designed and developed to modify planned
recesses for each agent. Then, optimal solutions were obtained by performing
simulation together with direct-search methods. The proposed procedure was
applied to a real case in order to confirm its effectiveness.
Using Simulation for Economic Policy Analysis in
the Global Agricultural Supply Chain
James N. Barnes (Louisiana
State University) and Nicholas G. Kalaitzandonakes and Thomas J. Crowe
(University of Missouri)
Abstract:
The purpose of this paper is to demonstrate how
discrete simulation can be used to measure the impact regulation has on
business processes and therefore contractual costs in global agricultural
supply chains. In particular, we examine how regulation of genetically
modified organisms (GMOs) in the European Union (EU) affects the cost of
contracting for soybean supplies between farmers and grain elevator firms in
the U.S. Using a simulation model of business processes at a grain elevator
operation, we examine how sensitive contract costs are to changes in a purity
threshold for non-GMO content set by EU regulation. Results indicate elevator
business processes are extremely sensitive to changes in non-GMO thresholds.
Even at small changes in purity, contracting costs varied between $0.04-0.09
cents per bushel. The implication is regulation of GMOs might protect EU
consumer rights, but protection may be costly and borne by agribusinesses in
the U.S. agricultural supply chain.
Supporting Simulation-based Decision Making with
the Use of AHP Analysis
Luis Rabelo, Hamidreza Eskandari, Tarek
Shalan, and Magdy Helal (University of Central Florida)
Abstract:
Traditionally decisions made based on simulation models
have been the outcomes of complicated statistical analyses and having
confidence in them is a subjective matter. Hybrid simulation offers an
improved approach to better model real life systems and increase confidence in
their outcomes. In particular hybrid discrete-continuous simulation has the
potentials to reduce the impact of statistics in building models in addition
to other significant benefits. In this paper we use hybrid models of
discrete-event simulation and system dynamics to analyze global supply chain
decisions. And to increase the decision makers’ confidence as well as to make
use of their experiences we apply the Analytic Hierarchical Process (AHP)
analysis to the simulation results in order to reach better decisions. We
describe the benefits of the use of the hybrid simulation and the added
advantages of using AHP in order to maximize shareholder value.
An Integrated And Adaptive Decision-Support
Framework For High-Tech Manufacturing And Service Networks
Peter
Lendermann, Malcolm Yoke Hean Low, Boon Ping Gan, Nirupam Julka, and Lai Peng
Chan (Singapore Institute of Manufacturing Technology), Stephen J. Turner,
Wentong Cai, and Xiaoguang Wang (Nanyang Technological University), Loo Hay
Lee (National University of Singapore), Terence Hung (Institute of High
Performance Computing), Simon J. E. Taylor (Brunel University), Leon F.
McGinnis (Georgia Institute of Technology) and Stephen Buckley (IBM Research)
Abstract:
This article describes the results of one of the ten
pilot programmes under the Integrated Manufacturing and Service Systems (IMSS)
initiative pursued by the Agency for Science, Technology and Research (A*STAR)
in Singapore. The objective of this particular programme is to investigate how
design, analysis, enhancement and implementation of critical business
processes in a manufacturing and service network can be realised using one
single simulation/application framework. The overall architecture of the
framework outlines how commercial simulation packages and web-service based
business process application components would have to be connected through a
commercial application framework to achieve maximum leverage and re-usability
of the applications involved. In the pilot phase of this programme, research
issues were also addressed with regard to mechanisms for interoperation
between commercial simulation packages, symbiotic interaction between
simulation-based decision support components and physical systems, and
simulation speed-up through multi-objective optimal computing budget
allocation techniques on a grid infrastructure.
Using Workflow Business Process Tools in
Simulation Modeling
John G. Everton and Richard D. Stafford (Brooks
Automation)
Abstract:
This article will present several model automation
strategies used to improve the modeling operations such as data maintenance,
model analysis and model visualization. There are several new products that
have emerged in academics and industry that help reduce the costs of
simulation and provide a solution that obtains more ROI from a new and/or
existing simulation model. In addition these modeling techniques provide the
capability to make models an operational component of a manufacturing system.
As an operational component, models can provide planned work schedules,
prediction estimates, and an operational decision tool that engineers and
managers can used in making better operational decisions.
On Developing System Dynamics Model for Business
Process Simulation
Lianjun An and Jun-Jang Jeng (IBM Watson
Research Center)
Abstract:
Business operations can be formally described in
business process models that capture activities, information, and flow
embedded in business operation. System dynamics modeling is a set of
conceptual tools that enable business process designers to build computer
simulations of complex business process behaviors. System dynamics models
provide accurate description of system behavior along the time dimension. It
gives a convenient tool to conduct what if analysis though dynamics points of
view. However, to develop system dynamics models requires keen understanding
of the “physics” of the target business operations, business organizations,
and financial structures and so on. This paper is aimed to provide heuristics
and guidelines of developing system dynamics models based on given business
process models along with associated reference contexts. An example, from
supply chain management domain, of using business process models to derive
system dynamics models will be given in the paper.
