WSC 2007 Final Abstracts

General Applications Track

Monday 10:30:00 AM 12:00:00 PM
Special Topics I

Chair: D.J. Medeiros (The Pennsylvania State University)

Validation of Simulated Real World TCP Stacks
Sam Jansen and Anthony McGregor (University of Waikato)

The TCP models in ns-2 have been validated and are widely used in network research. They are however not aimed at producing results consistent with a TCP implementation, they are rather designed to be a general model for TCP congestion control. The Network Simulation Cradle makes real world TCP implementations available to ns-2: Linux, FreeBSD and OpenBSD can all be simulated as easily as using the original simplified models. These simulated TCP implementations can be validated by directly comparing packet traces from simulations to traces measured from a real network. We describe the Network Simulation Cradle, present packet trace comparison results showing the high degree of accuracy possible when simulating with real TCP implementations and briefly show how this is reflected in a simulation study of TCP throughput.

Effective Workforce Lifecycle Management Via System Dynamics Modeling and Simulation
Lianjun An and Jun-Jang Jeng (IBM T. J. Watson Research Center), Changrui Ren (IBM China Research Laboratory) and Young M. Lee (IBM T. J. Watson Research Center)

Efficiently planning and managing workforce is a challenge imposed on many companies, especially for those in the service industry. The target of an effective workforce management is to recruit, develop and deploy the right people at the right places at the right times to fulfill both organizational and individual objectives. In this paper, we propose a novel concept of "workforce supply chain" to address the workforce management issue by considering both the demand side issue, i.e., project management, and the supply side issue, i.e., the human resource manage-ment. We then use System Dynamics modeling technique to capture the causality relationships and feedback loops in the workforce supply chain with the merit of system thinking. The evaluation of System Dynamics-based simulation exposes dynamic behavior and workforce management system and shows how adaptive control can be applied to such system.

Parallel Cross-Entropy Optimization
Gareth Evans (University of Queensland), Jonathan Keith (Queensland University of Technology) and Dirk Kroese (University of Queensland)

The Cross-Entropy (CE) method is a modern and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are highly complex and can take weeks or even longer to solve using current optimization techniques. This paper presents a general method for designing parallel CE algorithms for Multiple Instruction Multiple Data (MIMD) distributed memory machines using the Message Passing Interface (MPI) library routines. We provide examples of its performance for two well-known test-cases: the (discrete) Max-Cut problem and (continuous) Rosenbrock problem. Speedup factors and a comparison to sequential CE methods are reported.

Monday 1:30:00 PM 3:00:00 PM
Business Performance

Chair: Richard Wysk (The Pennsylvania State University)

Predicting the Impact on Business Performance of Enhanced Information System Using Business Process Simulation
Yifei Tan and Soemon Takakuwa (Nagoya University)

The estimation of the impact on performance in business process (BP) by introducing an information system (IS) is an important practical problem in investment appraisal. This paper quantitatively investigates the potential of business process simulation (BPS) as an approach for evaluating an expected IS impact on business performance. By introducing the ability to incorporate system variability, scenario analysis, and visual display to communicate process performance, BPS fundamentally enhances process performance analysis and makes it a useful technique providing a realistic evaluation of impact before introducing a particular IS. A real-life case study is discussed, showing how to develop a BPS model in helping analysts and decision makers arrive at more informed choices for systems design and evaluation.

Using Intelligent Agents to Understand Management Practices and Retail Productivity
Peer-Olaf Siebers and Uwe Aickelin (University of Nottingham) and Helen Celia and Chris Clegg (University of Leeds)

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.

iFAO-Simo: A Spatial-Simulation Based Facility Network Optimization Framework
Ming Xie, Wei Wang, Wenjun Yin, and Jin Dong (IBM China Research Laboratory)

This paper describes an innovative framework, iFAO-Simo, which integrates optimization, simulation and GIS (geographic information system) techniques to handle complex spatial facility network optimization problems ever challenged from retailing, banking and logistics nowadays. At the top level of iFAO-Simo, an optimization engine serves to generate and test candidate solutions iteratively by use of optimization algorithms such as Tabu Search and Genetic Algorithms. For each scenario given by the candidate solutions, a discrete event simulation engine is triggered to simulate customer and facility behaviors based on a GIS platform to characterize and visualize the spatial, dynamic and indeterministic environments. As the result, the target measures can be easily calculated to evaluate the solution and feedback to the optimization engine. This paper studies a real case of banking branch network optimization problem, and the results show that iFAO-Simo provides a useful way to handle complex spatial optimization problems.

Monday 3:30:00 PM 5:00:00 PM
Business Services Models

Chair: Stephen Buckley (IBM)

Discrete Event Simulation Modeling of Resource Planning and Service Order Execution for Service Businesses
Young M. Lee, Lianjun An, Sugato Bagchi, Daniel Connors, Shubir Kapoor, and Kaan Katircioglu (IBM T. J. Watson Research Center) and Wei Wang and Jing Xu (IBM China Research Lab)

In this paper, we present a framework for developing discrete-event simulation models for resource-intensive service businesses. The models simulate interactions of activities of demand planning of service engagements, supply planning of human resources, attrition of resources, termination of resources and execution of service orders to estimate business performance of resource-intensive service businesses. The models estimate serviceability, costs, revenue, profit and quality of service businesses. The models are also used in evaluating effectiveness of various resource management analytics and policies. The framework is aided by an information meta-model, which componentizes modeling objects of service businesses and allows effective integration of the components.

Simulation of Adaptive Project Management Analytics
Kaan Katircioglu, Lea A. Deleris, Sugato Bagchi, Shubir Kapoor, Richard B. Lam, and Steve Buckley (IBM T J Watson Research Center)

Typically, IT projects are delivered over-budget and behind schedule. In this paper, we explore the effects of common project management practices that contribute to these problems and suggest a better alternative that can utilize resources more effectively. Our alternative approach uses a thorough analysis of risks affecting activities in a project plan (i.e., the root factors leading to cost and time overruns), and an optimization of the resources allocated to each activity in the project plan to maximize the probability of on time and within budget project completion. One key feature of our method is its capability to adapt and learn the risk factors affecting activities during the course of the project, enabling project managers to reallocate resources dynamically to ensure a better outcome given the updated risk profile. We use simulations to test the performance of our optimization algorithm and to gain insights into the benefits of adaptive re-planning.

Agent-based Simulations of Service Policy Decisions
Richard B. Lam (IBM T J Watson Research Center)

During service engagements, project managers frequently encounter resource constraint issues. For each resource shortfall encountered, a project manager must decide among a narrow set of alternatives, weighing the resulting effects on project schedule, cost, and customer satisfaction. If a project is part of a larger collection of similar service engagements, it is less clear what the optimal strategy across all projects should be in deciding between alternatives. This paper describes an agent-based simulation environment to explore decision-making policies for hypothetical service business models using different agent-policy combinations. Results suggest advantages for maintaining flexibility in handling resource shortfall actions.

Tuesday 8:30:00 AM 10:00:00 AM
Call Centers

Chair: Eric Swenson (The Pennsylvania State University)

Using Simulation to Predict Market Behavior for Outbound Call Centers
Paulo J Freitas Filho, Geovani Ferreira Cruz, Rui Seara, and Guilherme Steinmann (Federal University of Santa Catarina)

In the last few years, the call center industry has considerably grown especially the outbound call center area, such as telemarketing. The productivity of the call centers has significantly increased, but they still require improvements especially because of the need to adapt their operations in some countries, like the UK and the USA, in which the silent calls are strictly regulated. For this reason, electronic dialer systems, termed predictive dialers, have been developed. Several of them have achieved good performance only under some special conditions. This paper intends to show how simulation models can be used as a predictive tool to forecast the outbound call center behavior aiming to build up a predictive dialer.

Partial Cross Training in Call Centers with Uncertain Arrivals and Global Service Level Agreements
Thomas R. Robbins, D. J. Medeiros, and Terry Harrison (Pennsylvania State University)

Inbound call center operations are challenging to manage; there is considerable uncertainty in estimates of arrival rates, and the operation is often subject to strict service level constraints. This paper is motivated by work with a provider of outsourced technical support services in which most projects (client specific support operations) include an inbound tier one help desk subject to a monthly service level agreement (SLA). Support services are highly specialized and a significant training investment is required, an investment that is not transferable to other projects. We investigate the option of cross training a subset of agents so that they may serve calls from two separate projects, a process we refer to as partial pooling. Our paper seeks to quantity the benefits of partial pooling and characterize the conditions under which pooling is most beneficial. We find that low levels of cross training yield significant benefit.

A Model for Contact Center Analysis and Simulation
Juan M. Huerta (IBM T. J. Watson Research Center)

In this paper we depart from a set of simple assumptions regarding the behavior of a pool of customers associated with an enterprise's contact center. We assume that the pool of customers can access the contact center through an array of communication modalities (e.g., email, chat, web, voice). Based on these assumptions we develop a model that describes the volume of demand likely to be observed in such an environment as a function of time. Under the simple initial assumptions, the model we develop corresponds to a mean-reverting process of the type frequently used in energy options pricing. When independence assumptions are relaxed and correlations between user behavior are included, a jump-diffusion component appears in the model. The resulting model constitutes the potential foundation for key simulation-based analyses of the contact center, like capacity modeling and risk analysis.

Tuesday 10:30:00 AM 12:00:00 PM

Chair: Martin Fischer (Noblis)

Modeling the Performance of Low Latency Queueing for Emergency Telecommunications
Denise M. Masi, Martin J. Fischer, and David A. Garbin (Noblis)

Event simulation and analytic modeling are used to evaluate the performance of Low Latency Queueing (LLQ), a queueing discipline available in some Internet packet switching routers for integrated services performance assurance. LLQ combines priority queueing with Class-Based Weighted Fair Queueing (CBWFQ). Priority queueing is used to ensure satisfying tight delay constraints for real-time traffic, whereas CBWFQ is used to ensure acceptable throughput for traffic classes that are less sensitive to delay. Simulations are developed both using a commercial product, OPNET Modeler, and also custom simulators that we developed. Our custom simulators model two different approaches to CBWFQ; and comparisons between the approaches and that of the commercial simulator are conducted. Our computational experiences in using the simulators are described. This work is an important first step in the ability to model a proposed enhancement to LLQ which may be beneficial to Emergency Telecommunications Services.

Using Event Simulation to Evaluate Internet Protocol Enhancements for Special Services
David A. Garbin (Noblis), Patrick McGregor (Nyquetek, Inc) and Denise M. Masi (Noblis)

Disasters can cause extraordinary service demand by the public, while concurrently causing outages that reduce network capacity to serve the surging demand. It is imperative that services supporting disaster response management perform with minimal degradation during such events. Mechanisms exist within Internet Protocol (IP)-based net-works to provide preferential treatment for services such as voice and video using Differentiated Services Code Points (DSCP) in the packet headers and Per Hop Behaviors in the routers. However, there is currently no way to identify voice and video packets supporting response management and to ensure their timely delivery during network overload periods. We have applied simulation to evaluate the benefit of additional DSCP markings to be applied to such voice and video packets, and several router configurations. The results demonstrate significant value of the additions in preserving disaster response management performance even when aberration in demand causes ordinary voice and video performance to degrade.

J-saedes: A Java-based Simulation Software to Improve Reliability and Availability of Computer Systems and Networks
Angel A. Juan (Technical University of Catalonia), Javier Faulin (Public University of Navarre), Joan Manuel Marques (Open University of Catalonia) and Mateo Sorroche (Technical University of Catalonia)

Nowadays, many companies rely on computer systems and networks for functions such as order entry, customer support, supply chain management, and employee administration. Therefore, reliability and availability of such systems and networks are becoming critical factors for the present-day enterprise or institution. Nevertheless, the task of determining reliability/availability levels for time-dependent systems and networks at the design stage can be: (a) extremely difficult to perform - mainly due to the system/network complexity, and (b) expensive, both in terms of necessary time and money. In this paper, we present a Java-based software, J-SAEDES, which makes use of discrete-event simulation to: (i) estimate reliability and availability of time-dependent computer systems and networks, (ii) identify those components that play a critical role in the system/network reliability or availability, and (iii) obtain additional information on some system/network perform-ance variables. An application example shows some potential uses of this software.

Tuesday 1:30:00 PM 3:00:00 PM
Special Topics II

Chair: Daniel Finke (The Pennsylvania State University)

Simio: A New Simulation System Based on Intelligent Objects
Claude Dennis Pegden (Simio Corp.)

Over the history of discrete event simulation the growth in applications has been facilitated by some key advances in modeling. Three important advances have been: the paradigm shift from an event to a process orientation, the shift from programming to graphical modeling, and the emergence of animation. These advances were made 25 years ago and provided the foundation for the current set of tools that are in use today. The past 25 years has been a period of evolutionary improvements with no significant advances in the core approach to modeling. The tools that are in use today are refined versions of what existed 25 years ago. This paper describes a new modeling system Simio - that is a departure from the design of existing tools with the aim of improving the activity of model building by promoting a paradigm shift from the process orientation to an object orientation.

Combining Network Reductions and Simulation to Estimate Network Reliability
Abdullah Konak (Penn State Berks)

Network reduction techniques are mainly used with exact approaches such as factoring to compute network reliability. However, exact computation of network reliability is feasible only for small sized networks. Simulation is an alternative approach to estimate network reliability. This paper discuses the effect of using network reductions before estimating network reliability using a simulation. Theoretical and empirical results are provided to understand the source of variance reduction in simulation due to network reductions.

Using Monte-Carlo Simulation for Automatic New Topic Identification of Search Engine Transaction Logs
Seda Ozmutlu, Huseyin Cenk Ozmutlu, and Buket Buyuk (Uludag University)

One of the most important dimensions of search engine user information seeking behavior and search engine research is content-based behavior, and limited research has focused on content-based behavior of search engine users. The purpose of this study is to present a simulation application on information science, by performing automatic new topic identification in search engine transaction logs using Monte Carlo simulation. Sample data logs from FAST and Excite are used in the study. Findings show that Monte Carlo simulation for new topic identification yields satisfactory results in terms of identifying topic continuations, however the performance measures regarding topic shifts should be improved.

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