WSC 2007 Final Abstracts

Poster Session Track

Sunday 6:00:00 PM 7:30:00 PM
General Posters

Chair: Earnest Foster (General Motors)

Mathematical Models and Simulation for Project Portfolios Optimization
Rongzeng Cao, Wei Ding, and Bonnie Ray (IBM China Research Lab)

Most organizations do not have sufficient resources to meet all of their obligations; selecting which projects should be funded is not just ranking projects and funding them "top-down" until resources are depleted. Organizations need to balance the benefits that project portfolios provide with their respective constraints and they need to do so in a meaningful way. To address this problem, we propose using enterprise portfolio analysis to reach the optimal projects mix and maximize the collective benefits, while balancing other factors such as risk, dependency and budget etc. Three extended mathematical models and revised dynamic programming algorithms together with simulation optimization are proposed based on solution of standard knapsack problem. Specifically, the proposed models and algorithms are illustrated using an example from practices.

Comparison of On-line Scheduling Algorithms: Quantifying the Effects of Shared Information Using a Simple Supply Chain Model
Jairo Montoya-Torres (Universidad de La Sabana) and Gloria Rodriguez-Verjan (Pontificia Universidad Javeriana)

Well-known information is essential for maintaining the market enterprise position and for getting the global performance success in the supply chain. In this paper, we are interested on the analysis, at the operational level, of the production scheduling problem of a manufacturer in a dynamic supply chain context. We consider a simple supply chain, whose members are modeled in an aggregated way and considered as "single-resources". We compare the performance of various scheduling algorithms implemented to solve different scenarios of information sharing among the actors of the chain. Information sharing situations using "look-ahead" algorithms are compared with "myopic" ones from the literature in order to get some insights about the impact of future shared information on the performance of dynamic production scheduling strategies. Our results suggest an interesting improvement that shows the importance of sharing future information without a considerable computational effort.

Castelldefels Project: Modeling and Simulation of the Computer System That Gives Support to the Virtual Campus of the Open University of Catalonia
Angel A. Juan (Technical University of Catalonia), Javier Faulin (Public University of Navarre) and Joan Manuel Marques and Pau Fonseca (Open University of Catalonia)

In this paper we present a case study regarding the modeling and simulation of a real computer system called Castelldefels. This system gives support to the Virtual Campus of the Open University of Catalonia (UOC), an online university that offers e-learning services to thousands of users. After analyzing several alternatives, the OPNET software was selected as the convenient tool for developing this network-simulation research. The main target of the project was to provide the computer system's managers with a realistic simulation model of their system. This model would allow the managers: (i) to analyze the behavior of the current system in order to discover possible performance problems such as bottlenecks, weak points in the structure, among others, and (ii) to perform what-if analysis regarding future changes in the system, including the addition of new Internet-based services, variations in the number and types of users, changes in hardware or software components.

Economic Assessment of Energy Systems with Simulation and Linear Programming
Fermin Mallor, Cristina Azcarate, and Rosa Blanco (Public University of Navarre)

Energy systems based on some natural renewal sources have the drawback of a random input, making them a non reliable supplier of energy. The regulation of the produced energy requires the introduction of new equipment able to storage this energy. The advantage of these transformation-storage systems is that the energy can be sold when the demand is higher and then also the prices are higher. The disadvantages are two, the costs of the new equipments and the lost of energy because of inefficiencies in the transformation processes. Our purpose is to develop a simulation model useful to the economic assessment of this type of energy systems. We also consider the analysis of optimal management policies, which are obtained by solving linear programming problems.

A Conceptual Model to Support the Integration of Inter-organizational Healthcare Information Systems
Hongmei Chi (Florida State University) and Lang Zhao (Florida A&M University )

The inability to share information across systems is just one of the major impediments in the health care business that hinders progress towards efficiency and cost-effectiveness. This poster investigates workflow involvement of healthcare process in order to support and complement the transition of information and tasks among different healthcare organizations. This research examined dataflow between organizations. The purpose of this study is to propose a conceptual model for integrating healthcare information systems of various healthcare organizations. A case study among pharmacy, hospital and clinic is presented in this paper. Our experimental results show that this model is scalable and it can be easier to extend to pervasive computing environment. Petri net is the primary method for this model.

Application of the Traveling Salesman Problem Heuristics to the Reallocation of Equipment in a Small-Size Bakery Aiming at Minimizing Bread Production Time
Chin Yung Shih, Anselmo R. P. Neto, and Eduardo V. G. Filho (School of Engineering of Sao Carlos)

This paper presents a case study of a small-size bakery whose problem is the reallocation of production equipment. The owner of the establishment intends to modify the current position of the warehouse, since raw material must be handled along the production system in order to be stored, jeopardizing the motion of bakers. This modification, though, would affect the location of the remaining equipment. The reallocation of the warehouse and equipment, obtained via the application of the travelling salesman problem heuristics, will reduce the total distance covered by the bakers, thereby avoiding the flow of raw material throughout the production system, and possibly increasing throughput. Before the implementation of the solutions generated by the heuristics, two simulation models will be created in Arena software 5.0, one representing the current configuration, and the other representing the proposed configuration, so as to validate the results.

Modeling The Indiana Coal Rail Transportation Infrastructure
Thomas Brady (Purdue University North Central)

The United States possesses a vast railroad infrastructure. Nearly one hundred forty thousand miles of rail exist across the country that are shared by over five hundred railroad companies. The railroad infrastructure is a driving force in the globalization of the US economy. As cross country container traffic has increased, traditional rail transport commodities such as coal have been forced to compete for scarce locomotive and track right resources. This competition has increased the cost of coal transportation. The state of Indiana ranks ninth nationally in the number of miles of railroad tracks. Indiana also possesses vast coal reserves. This paper presents the results of a project that used simulation to examine the coal transportation rail infrastructure capacity in the state of Indiana from the standpoint of increasing coal exports.

Combining Latin Hypercube Designs and Discrete Event Simulation in a Study of a Surgical Unit
Christian Dehlendorff, Murat Kulahci, and Klaus Kaae Andersen (Technical University of Denmark)

In this article experiments on a discrete event simulation model for an orthopaedic surgery are considered. The model is developed as part of a larger project in cooperation with Copenhagen University Hospital in Gentofte. Experiments on the model are performed by using Latin Hypercube Designs. The parameter set consists of system settings such as use of preparation room for sedation and the number of operating rooms, as well as management decisions such as staffing, size of the recovery room and the number of simultaneously active operating rooms. Sensitivity analysis and optimization combined with meta-modeling are employed in search for optimal setups. The primary objective in this article is to minimize time spent by the patients in the system. The overall long-term objective for the orthopaedic surgery unit is to minimize time lost during the pre- and post operation activities for acute and elective surgery as well as dedicated elective surgery.

Flight Time Allocation for a Fleet of Aircraft through Reinforcement Learning
Ville Mattila (Helsinki University of Technology)

Fighter aircraft are typically maintained periodically on the basis of cumulated usage hours. In a fleet of aircraft, the timing of the maintenance therefore depends on the allocation of flight time. A fleet with limited maintenance resources is faced with a design problem in assigning the aircraft to flight missions so that the overall amount of maintenance needs will not exceed the maintenance capacity. We consider the assignment of aircraft to flight missions as a Markov Decision Problem over a finite time horizon. The average availability of aircraft is taken as the optimization criterion. An efficient assignment policy is solved using a Reinforcement Learning technique called Q-learning. We compare the performance of the Q-learning algorithm to a set of heuristic assignment rules using problem instances that involve varying number of aircraft and types of periodic maintenance. Moreover, we consider the possibilities of practical implementation of the produced solutions.

POD: The Structure of Simulation Software and Model Reuse
Yariv N. Marmor and David Sinreich (Technion - Israel Institute of Technology)

In recent years, Discrete Event Simulation (DES) has emerged as the key technology for the design and analysis of systems, both in manufacturing and services. We have developed a DES-methodology (POD) and a tool that enable the automatic creation of a POD script from a working simulation model and backwards. POD stands for Processes, Operations and Data, to emphasize three key dimensions that differentiate DES systems from each other. It facilitates the generalization of models and the reuse of existing models for additional purposes with only minor changes, namely adjusting (copying, pasting, or deleting) the details of the POD script. Using different system components through copying and pasting of several generic components, then running and checking the system, deciding if to reject or retry the process, etc., enhances the learning process of the system and integrates naturally with its modeling.

Randomless as a Critical Point: Simulation Fitting Better Planning of Distribution Centers
Marcelo K. Fugihara and Alain d'Audenhove (Belge Engenharia) and Neuton T. Karassawa (Ryder Logistics)

The proposal of this paper is to show the importance of using simulation technology in logistic operations studies for a Distribution Center (DC). In addition, it will be presented a way as simulation technology can generate several benefits in distribution centers projects, such as providing a better resources and equipment sizing, number of docks for inbound and outbound, flow of materials, layout, etc., preventing common sizing errors when using only static analysis with spread sheets. In the last four years, besides the project made by Belge at Ryder Logistics, we developed several simulation projects for DCs in other companies like Unilever, Mclane, DHL-Exel and observed that previous statics analysis typically implies in errors varying between 20% to 60% when comparing with dynamic studies (simulated models) and the real implementations.

Comparing the Use of Discrete-Event Simulation and System Dynamics Models
Antuela A. Tako and Stewart Robinson (University of Warwick)

System Dynamics (SD) and Discrete-Event Simulation (DES) are two simulation approaches widely used in Operational Research. Existing literature on how these approaches compare is scarce. The few comparative studies found in the literature are mostly based on the authors’ personal opinions. Bringing the end user into the picture can give interesting insights about how differently users perceive DES and SD simulation models. This paper provides an empirical study on the comparison of the two simulation approaches in terms of model use. We used a questionnaire survey with executive MBA students in order to assess how different users find the two simulation approaches in terms of understanding, complexity, model validity, model usefulness and model results. Our results suggest that model users do not perceive any significant differences between a DES and SD model.

DEVS Specification and Implementation of SIMAN Blocks Using Modelica Language
Victorino Sanz, Alfonso Urquia, and Sebastian Dormido (UNED)

Modelica is a general object-oriented simulation language mainly based on non-causal modeling with mathematical equations. The aim of our work is to develop a Modelica library, ARENALib, for discrete process-oriented system modeling with comparable functionalities to Arena Basic Process panel. It will provide, combined with the current Modelica components for continuous system modeling, a good tool for modeling hybrid systems. A first version of the library, with basic capabilities, is freely available under GPL license. In this contribution an specification of the Create, Dispose, Queue, Seize, Delay and Release SIMAN blocks using DEVS formalism is presented. The implementation, in Modelica, of SIMANLib library is based on these specifications. Create, Process and Dispose modules of ARENALib have been reimplemented using SIMANLib blocks. A single server system model is also discussed. Future work will consist of the development of more SIMAN blocks to complete ARENALib modules and functionalities.

An Adaptive Metamodeling-based Method for Simulation Optimization
Maria Guadalupe Villarreal Marroquin and Mauricio Cabrera-Rios (Universidad Autonoma de Nuevo Leon)

In this work, a simulation optimization method is proposed. The method starts with an initial design of experiments with which an incumbent solution is obtained. At each iteration, a metamodel is obtained using the available set of points and it is used to generate a new attractive point where a simulation is performed. The simulated value of the new point is compared against the incumbent for updating purposes. A series of stopping criteria are evaluated and, if none is met, the new point is added to the existing set of points and a new iteration begins. Otherwise, the method stops. Preliminary results on the application of the method to several examples point towards a quick convergence to highly attractive solutions with a low number of simulations. The method is easy to follow and allows to be coded in a convenient manner to be run with low computational resources.

Simulation of the Pig Iron Transportation System in Companhia Siderurgica de Tubarao
Alain d'Audenhove and Bruno Miessa de Barros (Belge Engenharia e Sistemas)

The objective of this paper is to present the development of a simulation model involving materials handling in a large steel company from Arcelor Group. The project had a return of more than 2 million USD and points to a kind of application that seems to be a typical case where static analysis may cause great errors comparing to a dynamic one (because the results were also observed in another Brazilian steel company). The project focused in the processes involving pig iron transportation between the blast furnaces and its discharge in the steelmaking plant. It allowed the evaluation of several operational parameters such as for the 7.5 Mt/year production rhythm, a great increase from the actual production of 5 Mt/year. "Bottlenecks" in the flow were identified through the results and the scenarios gave the support to the decision of increasing the number of torpedo-cars and locomotives in the system.

Visual Support for Modeling and Simulation of Cell Biological Systems
Andrea Unger, Susanne Biermann, Mathias John, Adelinde M. Uhrmacher, and Heidrun Schumann (University of Rostock)

Cell biological systems are highly complex. They consist of many heterogeneously acting and interacting subsystems with various patterns of behavior, interaction and composition. To model and simulate these processes, new formalisms and algorithms are required which can represent the dynamic, multi-level structure. At this point new visualization techniques can serve for facilitating the understanding of models and data as well as for establishing and maintaining the communication with experts from other research fields like biology and medicine. To take a closer look at these potential applications we introduce a schema that outlines the iterative workflow from the wet lab experiments to the simulation model and its execution in a simulator. It moreover integrates comprehensive visual support for the analysis of experiments, the generation and analysis of the model, the analysis of simulation data, and the presentation of results to non-experts. First application-specific visualization techniques are presented as examples.

A Comparison Between System Dynamics And Agent Based Modeling And Opportunities For Cross-Fertilization
Luminita Stemate and Codrin Pasca (Defence R&D Canada Valcartier) and Ivan Taylor (Defence R&D Canada)

This work proposes a systematic approach to identify opportunities for cross-fertilization between two modeling paradigms: System Dynamics and Agent-Based Modeling. The motivation for this work is the authors' belief that there are gains to be made by crossing the boundaries between different domains of research, or different scientific approaches. This paper presents a comparison between the two modeling approaches, which is brought one step beyond the simple statement of the similarities and differences between them by introducing the novel aspect of taking a synergistic view specifically aimed at identifying a list of likely opportunities for cross-fertilization. The list presented here is not exhaustive and should be regarded more as a starting point than an ending point, and an invitation to other scientists to take such synergistic views even further.

Effectively Generating Random Test Data via Cellular Automata
Hongmei Chi and Edward L. Jones (Florida A&M University)

Testing is a costly process that is critical for assessing system behavior. Random testing is a widely used testing method. Generations of random test data are related to choices of random number generators. Whenever test cases are generated, a random number generator is chosen. This paper investigates the use of cellular automata, a generic algorithm, in the generation of test data. Based on knowledge of the geometric shape of the input domain and failure regions, we present methods for effective generation of test data by using cellular automata. In addition, we demonstrate by examples that cellular automata give an alternative method for generating test data in high dimensions.

SOA-Conform Modeling as a High-level Standard for Discrete Modeling and Simulation
Thomas Wiedemann (University of Applied Science Dresden)

The paper discusses a new and powerful approach by using Service Oriented Architectures (SOA). The integration of SOA-interfaces in simulation systems connects them to the common IT-infrastructure of ERP-systems, business process modeling systems and web-services. In addition, the SOA standards BPMN and BPEL are also capable for simulation modeling. So after 30 years without standards, the SOA technology can open a new chapter in discrete simulation.

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