WSC 2005 Final Abstracts

A Computer Simulation Model of Container Movement by Sea
Johan J. van Rensburg (CSIR) and Anton J. Kleywegt and Yi He (Georgia Institute of Technology)

Abstract:
We describe a computer simulation model of ocean container carrier operations. The simulation is called SimSea and was developed through collaboration between the CSIR, a research organisation in South Africa, and the Georgia Institute of Technology (Georgia Tech). SimSea simulates the transport of containers by container vessels. Containers are transported from container depots to customers. The customers load the containers, and thereafter the containers are transported to the ports. At the ports the containers are loaded onto and offloaded from vessels, and the vessels transport the containers between ports according to the vessels’ schedules. Containers are transported from the ports to receiving customers who unload the containers, and from there the empty containers are transported to container depots. Empty containers are also transported between container depots to compensate for imbalances in the flow of loaded containers.

Comparison of Three Automated Stacking Alternatives by Means of Simulation
Yvo A. Saanen (Delft University of Technology) and Margaret V. Valkengoed (TBA Nederland)

Abstract:
Container terminals are struggling with ever-increasing volumes, and are therefore searching for solutions to increase throughput capacity without expanding their physical footprint. They are also looking for cost-efficient solu-tions, leading to the application of semi-automated high density stacking systems for container storage. However, when selecting such a system, it needs to be determined what is the best configuration for that particular terminal, and secondly: how to make such a system productive? So far, we have seen various applications in practice that are quite different. How come? In this paper, we will compare three different automated container storage concepts on their efficiency in terms of productivity, flexibility, area utilization, and cost to come to a verdict: what is the best automated high-density concept yet existing? Furthermore, we will define the conditions under which a certain concept has to be preferred over another one.

Approach for Modeling of Large Maritime Infrastructure Systems
Edwin C. Valentin, Sicco Steijaert, and Rienk A. Bijlsma (Systems Navigator) and Piero Silva (Sogreah)

Abstract:
Simulation studies for large infrastructure systems often consists of a large number of experiments. Performing all experiments, and the required adjustments to simulation models, is time consuming. In addition it is difficult to keep track of all performed experiments and compare the outcome of these experiments. These issues can be clearly identified by observing a simulation study at the port of Tanger which is performed in the traditional way. In this paper we describe an alternative approach for performing simulation studies regarding large maritime infrastructure systems. This approach includes the use of a domain specific template developed in the simulation environment Arena and a database tool that enables creation, evaluation and managing simulation experiments.

Simulating Air Taxi Networks
Philippe A. Bonnefoy (Massachusetts Institute of Technology)

Abstract:
The U.S. air transportation industry is about to experience the emergence of on-demand air taxi networks enabled by a new generation of Very Light Jets (VLJs). These new networks are unique in many ways and the top down design approach of air taxi enterprises generates challenging and complex questions. Simulation was found to be an essential technique for understanding, analyzing and evaluating the complex behavior of air taxi networks. The Air Taxi Network Simulator is a fast-time simulator that replicates the operations of fleets of air taxi aircraft over a network of hundreds of airports. Its capabilities include demand modeling, trip generation, aircraft routing and pilot assignment, unscheduled maintenance events with recovery mechanisms, etc. It provides key performance metrics that enable decision makers to test and evaluate various strategic and tactical scenarios.

A Simulation-Based Architecture for Supporting Strategic and Tactical Decisions in the Apron of Rome-Fiumicino Airport
Giuseppe Confessore, Giacomo Liotta, and Rosario Grieco (National Research Council of Italy (ITIA-CNR))

Abstract:
In this paper we describe an architecture for the evaluation and optimization of aircraft ground movements in apron taxiways. The paper aims at providing an effective methodology for supporting the decision-makers involved in both the apron design and management phases. The purpose deriving from the utilization of the proposed approach consists in obtaining substantial improvements in the level of service with a reduction in congestion and ground delays within airports while considering safety aspects like aircraft separation. The methodology relies on a modular architecture. A simulation-based architecture, in which an optimization module is included, has been developed; an information feedback between simulation and optimization modules is enabled. The validation has been performed through the data of the apron of Rome-Fiumicino Airport. The computational results show a reduction in aircraft flowtime and a relevant decrease in aircraft ground flows. Interesting issues related to strategic modification of system configuration are presented.

Communication, Navigation, and Surveillance Events Simulation for the National Airspace
Paul T. R. Wang, Leonard A. Wojcik, and Scott B. Mayer (The MITRE Corporation)

Abstract:
The National Airspace System (NAS) is a large and complex system encompassing a wide-range of resources to enable safe and efficient air transportation. To effectively manage the NAS, it is very important to be able to reliably assess current and future demand for communications, navigation, and surveillance (CNS) resources as they are triggered by air traffic control (ATC) events. The authors present an integrated model that is capable of relating NAS ATC events to NAS CNS demand. Model validation with a subset of recorded ETMS CNS statistics will be presented. Combining such a model with NAS future demand predictors such as Terminal Area Forecasts (TAF) and Future Aviation Timetable Estimator (FATE), it becomes possible to estimate the increase in CNS demand and future requirements for CNS capacity, for resource planning purposes. The model presented in this paper includes tracking of radar-related messages and sector workload.

Modeling and Analysis of a Generic Cross-Docking Facility
Ghazi M. Magableh (Yarmouk University) and Manuel D. Rossetti and Scott Mason (University of Arkansas)

Abstract:
Many companies utilize a number of complex product distribution networks to transport various types of goods. Most of their distribution networks consist of transporting goods from their suppliers to their Distribution Centers (DCs). In the process of transporting goods from suppliers to DCs, cross docking facilities are utilized to consolidate loads in order to minimize costs. A simulation model of a generic cross-docking facility (CF) was developed to examine the operational risks associated with individual CFs within a company’s distribution network under a dynamic environment. The model was tested and validated on a large cross-docking facility. In addition, it was used to examine the effect of increasing demand through the cross-docking facility. The model is generic and can easily be expanded to model other cross-docking facilities.

Conceptual Simulation Modeling of Warehousing Operations
Ming Zhou and Kitti Setavoraphan (Indiana State University) and Zhimin Chen (Shenzho University)

Abstract:
This study focuses on the simulation modeling of warehousing operations commonly seen at general merchandize distribution centers. The key processes and their structural and behavioral characteristics were identified and analyzed. Robust representations and patterns were developed to represent the elements and logic of the simulation models for these processes to facilitate efficient and effective construction of the models. The issues of conceptual modeling such as synthesis, abstraction and specialization were also discussed.

Reservation Storage Policy for AS/RS at Air Cargo Terminals
Chulung Lee (Korea University), Huei Chuen Huang, Zhiyong Xu, and Bin Liu (National University of Singapore) and Paul Goldsman (Georgia Institute of Technology)

Abstract:
At air cargo terminals, the operations of an automatic storage and retrieval system (AS/RS) have certain special characteristics that both cargo arrival rates and storage duration are stochastic, and the probability distributions can only come from the empirical data. According to such particularities, this paper proposes a class-based reservation storage policy for AS/RS at air cargo terminals and an analytical model is developed. Two classes are investigated and a certain storage spaces are reserved for one priority class in such a way that the one-way travel time of S/R machine is minimized. The optimal reservation space is obtained by numerical searching. A simulation model is developed and the simulation results validate the optimal solution from the analytical model.

Upstream Demand Projection and Performance Mapping in Supply Chains
Rahul R Bagdia and Zbigniew J Pasek (University of Michigan)

Abstract:
This paper deals with modeling steady-state behavior of a single-product, pull-type, serial supply chain, frequently encountered in the automotive industries. The proposed analytical method enables projection of the end-customer demand information to upstream of the supply chain and estimate demand forecast at the individual tier levels. The supply chain performance assessment is based on the Due-Time Performance metric (DTP - probability to ship a required product/parts volume in a fixed time interval) under the assumption of customer demand following a discrete time Markov process, a special case for correlated demands. A numerical case study demonstrates the use of the DTP measure for a two-tier supply chain. The analytical results (verified by simulations) quantify important relationships in the supply chain, involving reliabilities of machines/stations, capacities of the buffers, demands correlation, and the due times and will find use in performance assessment, optimization and design of supply chains.

Risk Management in Supply Networks Using Monte-Carlo Simulation
Léa Amandine Deleris and Feryal Erhun (Stanford University)

Abstract:
Trends such as (1) globalization, (2) heavy reliance on transportation and communication infrastructures, and (3) lean manufacturing have led to an increase in the vulnerability of supply networks. Due to a large number of interrelated processes and products, disruptions caused by these vulnerabilities propagate rapidly. Firms, however, can partially control the robustness and resilience of their supply networks through strategic and tactical decisions. Therefore, a decision-support tool that assists managers to evaluate the risk exposure of their supply networks can considerably increase the robustness/resilience of these networks. In this study, we present a Monte Carlo simulation based tool designed to assess uncertainty in supply networks. We describe its application and discuss the possible drawbacks of our approach.

Stress Testing a Supply Chain Using Simulation
Sanjay Jain (The George Washington University) and Swee Leong (National Institute of Standards and Technology)

Abstract:
Simulation provides the capability to evaluate performance of a system operating under current or proposed configurations, policies and procedures. It is very applicable to evaluation of strategic and operational level plans for supply chains. It is especially useful for exploring the viability of a supply chain before beginning production. This paper describes the use of simulation for determining the readiness of a supply chain designed by a small company for providing sub-systems to a defense contractor. The supply chain had to be stress tested at surge and mobilization volume levels to meet the requirements. Simulation provided the ideal methodology to identify and demonstrate the behavior of the supply chain under stress and evaluate strategies to meet the defined volumes. It was used to prove the readiness of the supply chain reducing perceived risks in using the virtual operation.

A Simulation Environment for the Redesign of Food Supply Chain Networks: Integrating Quality Controlled Logistics
Jack G.A.J. van der Vorst and Seth Tromp (Wageningen University and Research Center) and Durk-Jouke van der Zee (University of Groningen)

Abstract:
Nowadays, many industries are confronted with intensified global competition as well as advances in information and process technology. They create both the need and opportunity for a coordinated approach of industrial partners to establish effective and efficient supply chains. Simulation tools are often used for supporting decision-making on supply chain (re)design, building on their inherent modeling flexibility. However, food supply chains set some specific requirements to simulation models. To address these demands a new discrete event simulation environment called ALADIN has been developed. It is based on a generic modeling framework that offers the analyst guidance in modeling, and provides model transparency to problem owners. An essential feature of the new tool concerns the integration of reusable process building blocks and quality decay models enabling “Quality Controlled Logistics”. A case example concerning a supply chain for peppers is pre-sented to illustrate the applicability and advantages of the tool.

Information Synchronization Effects on the Stability of Collaborative Supply Chain
Jayendran Venkateswaran and Young-Jun Son (The University of Arizona)

Abstract:
In this paper, the dynamics of a collaborative supply chain have been analyzed using transform techniques. The general conditions for stability of the supply chains are derived and the effects of inter-player sampling intervals are analyzed. System dynamics simulation models of the different members of the supply chain are developed. Z-transform techniques are employed to derive the general stability conditions (settings of control parameters that produce stable response). The variation in the supply chain’s stability in response to the information synchronization frequency is examined by relating the update frequency to the sampling interval of the underlying difference equations. Existence of instability due to improper parameter selection and improper sampling interval selection is thus confirmed, and guidance for the selection of appropriate parameters to guarantee system stability is presented. Simulations are used to confirm our analysis and help demonstrate the stable or unstable behavior of the supply chain.

Simulation Based Evaluation of Information-Centric Supply Chains
Srinagesh Gavirneni (Cornell University)

Abstract:
In this paper we evaluate, via the use of simulation, information-centric design of three supply chains that are ubiquitous in operations management literature. With emphasis on inventories, we show how such a redesign of the supply chains can significantly enhance the benefit from information flows that are commonplace in the current business world. The underlying analysis is in the realm of stochastic non-stationary capacitated inventory control and the mathematical intractability behooves us to make extensive use of simulation. We postulate that the lack of such information centric redesigning of supply chains is one of the main reasons behind the failure, reported in popular press, of most information gathering projects in the industry.

Application of Multi-objective Simulation-optimization Techniques to Inventory Management Problems
Loo Hay Lee, Suyan Teng, Ek Peng Chew, I. A. Karimi, Yankai Chen, and Choon Hwee Koh (National University of Singapore) and Kong Wei Lye and Peter Lendermann (Singapore Institute of Manufacturing Technology)

Abstract:
In this paper, we present how a solution framework developed for (a special case of) the multi-objective simulation-optimization problems can be applied to evaluate and optimally select the non-dominated set of inventory policies for two case study problems. Based on the concept of Pareto optimality, the solution framework mainly includes how to evaluate the quality of the selected Pareto set by two types of errors, and how to allocate the simulation replications according to some asymptotic allocation rules. Given a fixed set of inventory policies for both case study problems, the proposed solution method is applied to allocate the simulation replications. Results show that the solution framework is efficient and robust in terms of the total number of simulation replications needed to find the non-dominated Pareto set of inventory policies.

A Simulation Analysis of the Vari-Metric Repairable Inventory Optimization Procedure for the U.S. Coast Guard
Michael Batista Zamperini (U.S. Coast Guard Academy) and Michael Bowden Freimer (Penn State University)

Abstract:
This paper documents a simulation study undertaken to gain insights into the Vari-Metric multi-echelon repairable inventory optimization method. The method was analyzed in the context of the Coast Guard’s fleet of fixed and rotary wing aircraft, for which operational availability is the key performance metric. Failure rates of parts in this system exhibit variance-to-mean ratios higher than one, and we outline a procedure for generating a failure arrival process described by a negative binomial distribution. Previous studies of the Vari-Metric model examined a single repairable part; in this study we analyzed a system comprised of three repairable parts. This allowed us to gain insights into how the Vari-Metric procedure selects part stock levels to attain a desired level of system availability. Further analysis of the simulation model allowed us to examine the efficient frontier for this multi-criteria problem (maximizing spare part availability rates while minimizing the cost of part inventories).

Structure Modeling of Machine Tools and Internet-Based Implementation
Yoonho Seo, Dong-Pyo Hong, and Insu Kim (Korea University), Taiun Kim (Kyungsung University), Donmok Sheen (University of Ulsan) and Gyu-Bong Lee (KITECH)

Abstract:
Reconfigurability of machine tools is one of the critical factors to realize the responsive manufacturing systems to satisfy the mass-customization production. This paper presents the methods to model and simulate the machine tools on Internet in response to change in the machining requirements. Specifically, a set of module combination rules and a modeling method of the structure of machine tools using connectivity graph are developed. In response to the user requirements, kinematic relations and structures of machine tools can be derived using the module combination rules and connectivity graph relationships. Internet-based simulator of machine tools is implemented and presented. The developed machine tool simulator can be used to verify the structure of machine tools derived from the user requirements.

Optimal Lot Sizing in a Two-Stage System with Auto-Correlated Arrivals
Silvanus T. Enns and Ping Zhu (University of Calgary)

Abstract:
Most research on lot-size optimization has concentrated on single-stage batch production systems. However, in practice it is of interest to optimize performance over multiple processing stages, where stages are not independent. The models in this study consider two stages, where multiple products are produced using the processing stages sequentially. The objective is to minimize total lot flow times across both stages by selecting the optimal lot sizes for each product, subject to these remaining constant across both stages. Analytical relationships can be developed but rely on the assumption of lot interarrival time independence. This is clearly not the case in most manufacturing problems. Better solutions can be obtained experimentally using simulation and response surface methods. Alternatively, an approach has been developed that allows dynamic feedback to be used in adjusting analytical relations to compensate for auto-correlation. Results using this approach compare well with those obtained experimentally.

Simulating and Designing the Stochastic Inbound Inventory Routing Problem
Malini Natarajarathinam and Charles R. Sox (University of Alabama)

Abstract:
We consider the situation where parts from suppliers have to be picked up by a capacitated vehicle for an assembly plant that faces stochastic demand. We propose a two-phase heuristic to calculate “good” base stock policies for the stochastic inbound inventory routing problem. In this paper, we calculate multiple performance measures for the results obtained from the analytical model. The results show that the maximum average utilization of the vehicle is a significant factor in determining our fill rate. We consider several test cases to substantiate the results. The interactions between the performance measures for different situations are also discussed.

Discrete Event Simulation in Supply Chain Planning and Inventory Control at Freescale Semiconductor, Inc.
Douglas J. Morrice and Richard A. Valdez (The University of Texas at Austin) and Jack P. Chida, Jr. and Missan Eido (Freescale Semiconductor, Inc.)

Abstract:
The supply chain of Freescale Semiconductor from fabrication through final test and delivery was modeled and analyzed using discrete event simulation in Arena. Freescale starts products in manufacturing based on a make-to-order and make-to-stock master production schedule. Since customer lead time is often less than the supply chain cycle time, Freescale maintains strategic safety stock throughout the supply chain and as finished goods inventory. Manufacturing entry rate is determined by the amount of product in WIP and inventory. Our analysis concentrates on the relationship between on-time delivery in the major supply chain segments and on-time delivery to the customer in an environment of significant inventory and WIP level changes. The goal is to predict the effect of internal on-time delivery, inventory and WIP changes on the customer order fulfillment service level. In our analysis, we evaluate supply chain production and inventory control policies and the impact of lead time reductions.

Dynamic Simulation of a Push-pull Distribution System
Payman Jula and Mark S. Zschocke (University of Alberta)

Abstract:
This paper presents the methodology of the development and the results of a simulation model used to capture the complexities of sulphur distribution system run by Sultran Ltd. in Western Canada. Sulphur is a valuable by-product of natural gas which should be continuously transported from the gas plants to avoid plant shutdowns. The sulphur is routed via rail to port terminals, where ships with variable demands arrive. The empty cars are then assigned back to gas plants for reloading. This closed-loop rail transportation system is challenging to simulate due to the push-pull nature of the system, the high degree of variability, as well as the interdependency of simulated elements. The problem becomes even more challenging when we consider many tactical and operational policies. The developed model is used to study the results of different operations management policies and help the mangers make appropriate decisions.

Pull Systems with Advance Demand Information
Ananth Krishnamurthy and David Claudio (Rensselaer Polytechnic Institute)

Abstract:
This paper investigates the benefits of integrating advance demand information (ADI) with pull-kanban type production and inventory control systems (PICS). Since efficient analytical models for performance evaluation studies of these systems are unavailable, we use simulation experiments for the study. In particular, we investigate the impact of several PICS design parameters such as kanban card limits, target finished goods inventory levels, amount of demand information available, and the quality of ADI on performance measures such as system throughput, inventory holding costs and customer service levels. Our study shows that in many situations, integrating ADI with pull systems provides opportunities for efficiencies that might be significantly greater that that available using pull systems alone. Further more, we show that the performance of systems operating under pull-type PICS with ADI could be fairly robust to the quality of information being shared.

Newsvendor Problem with Pricing: Properties, Algorithms, and Simulation
Zuo-Jun Max Shen (University of California, Berkeley) and Roger Lezhou Zhan (University of Florida)

Abstract:
When a newsvendor faces stochastic price-sensitive demands, he/she has to make the pricing and inventory decisions before the demand is realized. In the literature, this problem is typically solved by reducing it to an optimization problem over a single variable. In contrast, we treat this problem as a nonlinear system of two variables and provide some solution properties (e.g. existence, uniqueness) of the system. We also develop an iterative algorithm and a simulation based algorithm for this problem.

Flexible Module-Based Modeling and Analysis for Large-Scale Transportation-Inventory Systems
Kanna Miwa and Soemon Takakuwa (Nagoya University)

Abstract:
A method of modeling large-scale transportation-inventory systems is proposed as an attempt to describe the systems flexibly. Such a system has a lot of items that are ordered, transported, and stored at the warehouses of the distribution centers. The system consists of any required numbers ofsources and destinations as the need arises to build a simulation model. The order by a destination is made toward the associated source, based on the inventory policy at the distribution center. A more flexible module-based method is proposed to generate simulation models for transportation-inventory systems and by adopting Excel VBA. The proposed method is applied to the actual system. It was found that the time to build simulation models could be drastically reduced. Furthermore, the proposed method was found to be both practical and powerful.

A Family of Market-based Shipment Methodologies for Delivery Supply Chain
Seog-Chan Oh (The Pennsylvania State University), Shang-Tae Yee (General Motors Research and Development Center), Soundar R. T. Kumara (The Pennsylvania State University) and Jeffrey D. Tew (General Motors Research and Development Center)

Abstract:
Load building is an important step to make the delivery supply chain efficient. We present a family of load makeup algorithms using market control-based strategy, named LoadMarket, in order to build efficient loads where each load consists of a certain number of finished products having destinations. LoadMarket adopts minimum spanning tree graph algorithm for generating initial endowment for Load Traders who cooperate to minimize either total travel distance or the variance with respect to the travel distances of loads through a spot market or double-sided auction market mechanism. For the simulated load shipment market, the efficiency of the LoadMarket algorithms is analyzed using simulation experiments.

A New Simulation Model for Expressway Weaving Sections Evaluation
Sun Jian, Yang Xiaoguang, and Ma Yunlong (Tongji University)

Abstract:
Simulation of traffic flow is an effective tool for traffic system management, control and optimization, particularly in congested urban areas. TESS is an object oriented traffic simulation model with detailed representation of vehicles and their interactions. This paper presents the TESS simulator including the car-following model and new lane-changing procedures. Four weaving sections are simulated in TESS platform using field data come from Traffic Information Collecting System in Shanghai China. Compared with the CORSIM model, good results are obtained after using the calibrated TESS model in simulating weaving sections.