WSC 2008

WSC 2008 Final Abstracts

Logistics, Transportation and Distribution Track

Monday 10:30:00 AM 12:00:00 PM
Maritime Transportation Systems

Chair: Bill Biles (University of Louisville)

A Simulation Approach to the Evaluation of Operational Costs and Performance of Liner Shipping Operations
Aldo McLean and William E. Biles (University of Louisville)

This paper presents a simulation model of the operation of a liner shipping network that considers multiple service routes and schedules. The objective is to evaluate the operational costs and performance associated with liner shipping, as well as the impact of individual service schedules on the overall system. The approach proposes a discrete-event simulation model where shipping activities, container ship operations, and intermodal container movements are considered. The model allows for direct and transshipment operations of container cargo, and the evaluation of fuel consumption and other logistics metrics. The model is used to evaluate a liner shipping network consisting of four service routes, up to 64 container ships, and up to 20 ports with diverse physical characteristics and cost components. The results show the contribution of service routes, ports, container ships, and containers to the cost and performance of the system.

Determination of Operating Policies for a Barge Transportation System through Simulation and Optimization Modeling
Nicholas Anderson (Mesoscale Diagnostics) and Gerald W. Evans (University of Louisville)

This paper presents a simulation model of a barge transportation system for petroleum delivery within an inland waterway. The simulation is employed as an evaluation model within a decision support system which also includes a criterion model, represented as a decision maker’s utility function, and an optimization procedure which employs scatter search. Variance reduction techniques are also employed in order to improve the accuracy of the estimates of the performance measures associated with the system. The main purpose of the system is to determine values for important inventory policy variables.

An Object-Oriented Programming Approach for a GIS Data-driven Simulation Model of Traffic on an Inland Waterway
Daniel Sasso and William E. Biles (University of Louisville)

This research proposes the integration of a Geographic Information System (GIS) with the Arena Simulation software to model the transit of ocean-going vessels through the Panama Canal. The purpose of this integration is to initialize the simulation model with the vessels that are currently transiting the system and the ones ready to begin their transit taking into account waiting time in queue, booking status, navigation restrictions and their times through the locks. The interface process consists of gathering vessel location and attribute data, which is loaded in database format in the GIS where it is analyzed and displayed in a map containing the location of the locks, anchorage areas, tie-up stations and the transit route. Once analyzed, Arena reads the GIS data from the database and proceeds with the simulation considering navigation transit time, locks transit and lockage times.

Monday 1:30:00 PM 3:00:00 PM
Supply Chain Simulations in Industry

Chair: Young Lee (IBM T.J. Watson Research Center)

Using Data Driven Simulation to Build Inventory Model
Minghui Yang (Boeing IMM Demand Forecast)

Many general-purpose simulation languages (such as ARENA, SLAM II, GPSS/H, SIMAN etc) have been the major simulation tools to simulate the demand-supply processes. They have made great contributions to the decision making. But in the recent years, followed by the fast development of WINDOW applications, powerful PC hardware and software, numerous applications have used different approaches to develop simulation applications. One rapidly developing area in simulation is dynamic data-driven simulation (DDDS) by using data manipulation and analysis packages. SAS is a powerful tool for data analysis and data manipulation. It can also be used to build simulation models in data driven applications. This article presents our research development in this area for demand forecast applications.

Analyzing Dispensing Plan for Emergency Medical Supplies in the Event of Bioterrorism
Young M. Lee (IBM T.J. Watson Research Center)

To prepare for the event of bioterrorism, which could spread contagious disease such as anthrax, plague, smallpox, or tularemia to public, local governments in the United States are required have a plan for dispensing medical supplies such as vaccines and antibiotics to general public. The mass prophylaxis would need to cover millions of people in large cities in a short period of time. The distribution and dispensing plan of the medical supplies have to be effective since it would influence health and lives of many people, and there would be no time to fix or adjust plan once the emergency event occurs. In this work, we develop a simulation model to help a major U.S. city in evaluating the effectiveness of alternative dispensing plans and identifying improvement opportunities. This paper describes potential risks and generalized recommendations that can lead to developing effective supply chain and dispensing plans.

Simulating Order Fulfillment and Supply Planning for a Vertically Aligned Industry Solution Business
Feng Cheng, Young M. Lee, Wei Wang, and Hongwei Ding (IBM Research) and Stuart Stephens (IBM Integrated Supply Chain)

We model supply chain of an industry solution equipment manufacturer, where the merchandise is sold worldwide, but suppliers are mostly located in Asia. The preferred shipment of supply is the ocean shipment, and it takes about 5 weeks. Premium air shipment can be used to expedite delivery, but it costs substantially higher. To hedge against variability of demand and to satisfy customer service level, a certain level of safety stock is needed but inventory carrying cost can be high. Therefore, a careful fulfillment strategy is very important to balance serviceability and cost. A supply chain simulation model is developed to analyze the order fulfillment and supply planning process for the business to identify efficient supply chain strategy. The model simulates and evaluates three key performance metrics; serviceability, inventory costs and premium transportation costs, and their interactions.

Monday 3:30:00 PM 5:00:00 PM
Simulation and Optimization in Logistics Systems

Chair: Malak Al-Nory (George Mason University)

Unifying Simulation and Optimization of Strategic Sourcing and Transportation
Malak Talal Al-Nory and Alexander Brodsky (George Mason University)

Proposed and developed is a framework and an extensible library of simulation modeling components for strategic sourcing and transportation. The components include items, suppliers, volume-discount schedules, aggregators, procurement rules, and less-than-truck-load delivery. Service models are classes in the Java programming language extended with decision variables, assertions, and business objective constructs. The optimization semantics of the framework is based on finding an instantiation of real values into the decision variables in the service object constructor, that satisfies all the assertions and leads to the optimal business objective. The optimization is not done by repeated simulation runs, but rather by automatic compilation of the simulation model in Java into a mathematical programming model in AMPL and solving it using an external solver.

Simulation-Based Optimization of a Complex Mail Transportation Network
Anna Syberfeldt, Henrik Grimm, Amos Ng, Martin Andersson, and Ingemar Karlsson (University of Skövde)

The Swedish Postal Services receives and distributes over 22 million pieces of mail every day. Mail transportation takes place overnight by airplanes, trains, trucks, and cars in a transportation network comprising a huge number of possible routes. For testing and analysis of different transport solutions, a discrete-event simulation model of the transportation network has been developed. This paper describes the optimization of transport solutions using evolutionary algorithms coupled with the simulation model. The vast transportation network in combination with a large number of possible transportation configurations and conflicting optimization criteria make the optimization problem very challenging. A large number of simulation evaluations are needed before an acceptable solution is found, making the computational cost of the problem severe. To address this problem, a computationally cheap surrogate model is used to offload the optimization process.

Simulation Based Optimization of Multi-Location Transshipment Problem with Capacitated Transportation
Banu Yetkin Ekren and Sunderesh S. Heragu (University of Louisville)

In this study, a single-item two-echelon inventory system where the items can be stored in each of N stocking locations is optimized using simulation. The aim of this study is to minimize the total inventory, backorder, and transshipments costs, based on the replenishment and transshipment quantities. In this study, transshipments which are the transfer of products among locations at the same echelon level and transportation capacities which are the transshipment quantities between stocking locations, are also considered. Here, the transportation capacities among the stocking locations are bounded due to transportation media or the locations’ transshipment policy. Assuming stochastic demand, the system is modeled based on different cases of transshipment capacities and costs. To find out the optimum levels of the transshipment quantities among stocking locations and the replenishment quantities, the simulation model of the problem is developed using ARENA 10.0 and then optimized using the OptQuest tool in this software.

Tuesday 8:30:00 AM 10:00:00 AM
Container Operations

Chair: Csaba Boer (TBA B.V.)

Controls: Emulation to Improve the Performance of Container Terminals
Csaba A. Boer and Yvo Saanen (TBA B.V.)

Nowadays container terminals are struggling with a continuously increasing volume. Therefore, they are searching for solutions to increase throughput capacity without expanding their physical footprint. Furthermore, they aim to increase their productivity on vessels in order to be able to handle bigger ships with larger call sizes in the same time frame. A terminal operating system (TOS) plays a major role in today’s terminal operations as it supports planning, scheduling and equipment control. Recently more and more tasks are performed by the TOS – stowage planning, grounding decisions, equipment dispatching – and therefore, they need to be well-tuned to the operation, which remains a terminal specific characteristic. In this paper, an approach is presented to test and tweak the TOS and train operators on a virtual terminal. The implementation of this approach has been successfully applied during several TOS update or replacement projects for Rotterdam, Hong Kong, Virginia and Antwerp.

Yard Crane Dispatching Based on Real Time Data Driven Simulation for Container Terminals
Xi Guo, Shell Ying Huang, Wen Jing Hsu, and Malcolm Low (Nanyang Technological University)

This paper studies the problem of real-time yard crane dispatching in container terminals. Many technologies, including transponders, RFID and GPS have been used in terminal settings for real-time tracking of terminal equipments. A judicious integration of real-time data into the yard crane management system will allow better utilization of terminal resources to improve overall terminal productivity. We propose a dispatching algorithm based on real time data driven simulation to solve the problem of yard crane job sequencing to minimize average vehicle waiting time. The algorithm produces optimal operation sequence for each planning window. Several policies to select jobs to form the planning window are proposed. Our simulation results show that dispatching yard crane based on real-time data driven simulation is of great value in improving yard crane performance in 3 scenarios with different vehicle arriving patterns and our results are 10% worse off a loosely estimated overall optimal performance results.

Generic Simulation for Rail-Road Container Terminals
Thouraya Benna and Manfred Gronalt (University of Natural Resources and Applied Life Sciences, Vienna)

Hinterland terminals enable the transshipment of containers between various modes of transport and play a significant role in intermodal freight transportation. In this paper we present a simulation-based tool, that can be used to plan and design a rail-road container terminal, by simulating different terminal configuration in advance and accessing performance and utilization limits of the planned terminal.

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

Chair: Sanjiv Shresta (The MITRE Corporation)

A Recursion-Based Approach to Simulating Airline Schedule Robustness
Marcial Lapp, Shervin AhmadBeygi, Amy Cohn, and Omer Tsimhoni (University of Michigan)

Flight disruptions due to events such as inclement weather or mechanical failure are an increasing occurrence in today’s air travel. It is important to develop flight schedules that are not only economically feasible, but also provide opportunities to absorb these disruptions so as to reduce downstream delays. In this paper, we present a simulation algorithm to evaluate a flight schedule’s ability to mitigate disruptions by analyzing propagation effects on the flight network. This task is challenging for two reasons: the interdependence of flights, due to shared resources (e.g. cockpit/flight crews, aircraft), and the cyclic nature of the schedule, which repeats on a daily basis. We show how a recursion-based approach to the simulation enables us to overcome these challenges.

Simulation of Unit Loading Device Inventory in Airline Operations
Chatabush Roongrat (University of Texas at Arlington)

Commercial airlines often encounter imbalances in their inventory of unit loading devices (ULDs). A stochastic simulation model was developed to evaluate inventory policies. The structure of the simulation model is described. We evaluate a minimum ULD loading configuration policy and demonstrate how it reduces ULD shortages and helps balance ULD network flow and inventory. As a result, airlines can reduce operating expenses and improve customer service. Finally, we give future directions for studying ULD inventory.

Modeling of Air Traffic Arrival Operations through Agent-Based Simulation
Sanjiv Shresta and Ralf H. Mayer (The MITRE Corporation)

This paper reports on the development and validation of an agent based simulation model of air traffic control arrival operations. The simulation model includes modeling of both the structure and procedures of air traffic operations. It is thus suitable for evaluating the impacts of shifts in those structures and procedures. Three key operational metrics are introduced which are sensitive to the internal workings of air traffic arrival operations. The simulation model is validated by demonstrating agreement in those key metrics between the simulation and a set of baseline arrival operations radar data. After the simulation model has been shown to reproduce actual operations, select details of the simulation can be altered to incorporate proposed operational changes. The impact of the changes on the computer simulation will offer a prediction of how the operational changes will affect actual operations.

Tuesday 1:30:00 PM 3:00:00 PM
Supply Chain Systems

Chair: Salvatore Cannella (University of Palermo)

The Apiobpcs Deziel and Eilon Parameter Configuration in Supply Chain Under Progressive Information Sharing Strategies
Salvatore Cannella and Elena Ciancimino (University of Palermo)

The aim of this paper is to investigate how different smoothing parameter levels of the Automatic Pipeline Inventory and Order Based Production Control System smoothing replenishment rule impact on the bullwhip dampening efficacy, under progressive information sharing strategies. The main results of this work are: (1) The smoothing parameter variations significantly impact on performance of the supply chains characterised by low information sharing level. (2) As smoothing parameters increase, the supply chain process performance improves and the customer service level worsens. This opposite trend noticeably decreases as information sharing level increases. (3) Amongst the bullwhip dampening techniques, deeper information sharing weights more than the value of smoothing parameters. The analysis is performed through continuous time differential equation modelling.

Multi-Echelon Supply Chain Simulation Using Metamodel
Laigang Song, Xueping Li, and Alberto Garcia-Diaz (University of Tennessee)

Metamodels are abstractions of the simulation model that expose the system's input-output relationship through simple mathematical expression. It provides an analytical way to study the behavior of a complex system. Multi-echelon supply chain are one of the complex systems. It is hard if not impossible to draw close-form analytical solutions due to the complexities of inventory system and the underlying uncertainty. In this paper, we will apply the methodology of simulation metamodel to a multi-echelon supply chain problem and make statistically analysis of the parameters. The model is validated using training experiment conditions.

An Introduction to IBM General Business Simulation Environment
Wei Wang, Jin Dong, Hongwei Ding, Changrui Ren, and Minmin Qiu (IBM China Research Laboratory) and Young M. Lee and Feng Cheng (IBM T. J. Watson Research Center)

IBM General Business Simulation Environment (GBSE) is a supply chain simulation tool developed by IBM China Research Lab. It can capture supply chain dynamics with finest level of granularity and provides great insights to a supply chain's real operations. GBSE is designed for tactical level decision making; it is proper for supply chain what-if analysis and risk analysis. GBSE implements multiple supply chain processes to considerable details, such as order handling process, inventory control process, manufacturing process, transportation process, procurement process, and planning. The environment is created as a desktop software tool based on Eclipse platform. The backbone framework consists of Presentation Layer, Controller Layer, Service Layer, and Data Layer.

Tuesday 3:30:00 PM 5:00:00 PM
Logistics Equipment Routing and Scheduling

Chair: Loo Lee (National University of Singapore)

SR-1: A Simulation-Based Algorithm for the Capacitated Vehicle Routing Problem
Javier Faulin (Public University of Navarre), Miquel Gilibert, Angel A. Juan, and Xavier Vilajosana (Open University of Catalonia) and Ruben Ruiz (Valencia University of Technology)

In this paper we present SR-1, a simulation-based heuristic algorithm for the Capacitated Vehicle Routing Problem (CVRP). Given a CVRP instance, SR-1 uses an initial “good solution”, such as the one provided by the classical Clarke and Wright heuristic, in order to obtain observations for the variable “distance between two consecutive nodes in a route”. These observations are then fitted by a statistical distribution, which characterizes the inter-node distances in good solutions. Then, the fitted distribution is employed to generate a large number of new random solutions with similar edge-size distribution. Thus, a random but oriented local search of the space of solutions is performed, and a list of “best solutions” is obtained. This list allows considering several properties per solution, not only aprioristic costs, which can be practically used when making multiple-criteria decisions. Several tests have been performed to discuss the effectiveness of this approach.

Simulation-Based Optimization for the Quay Crane Scheduling Problem
Pasquale Legato and Rina Mary Mazza (University of Calabria) and Roberto Trunfio (CESIC – NEC Italia S.r.l.)

Maritime terminals of pure transhipment are emerging logistic realities in long-distance containerized trade. Here, complex activities of resource allocation and scheduling should be optimized in a dynamic, non deterministic environment. The assignment of expensive quay cranes to multiple vessel-holds for container discharging and loading operations is a major problem, whose solution affects the operational performance of the whole terminal container. In OR literature, this problem is known as the quay crane scheduling problem. With the objective of minimizing the vessel’s overall completion time, we first give our IP formulation and then, under the more realistic assumption that discharge-loading times are non deterministic, we focus on a simulation-based optimization approach which embodies the IP formulation. Two different simulation optimization algorithms are tailored to the problem: simulated annealing and adaptive balanced explorative and exploitative search. Preliminary numerical results are presented on real vessel data.

A Study on Port Design Automation Concept
Loo Hay Lee, Ek Peng Chew, Haixing Cheng, and Yongbin Han (National University of Singapore)

In this paper, an automation concept is proposed to facilitate the simulation model building for port design problem. Currently, this process, which includes drawing the terminal layout and programming the simulation logic based on the drawn layout, is highly manual, very tedious and time-consuming. This makes the optimization of the port design very difficult because it involves too much manual process. Hence, we build an ALG (Automated Layout Generation) program to generate the simulation model automatically based on the input parameters provided by users. Besides, we integrate this program with simulation optimization algorithms, which can generate new designs, evaluate the designs efficiently and finally identify the promising designs.

Wednesday 8:30:00 AM 10:00:00 AM
Distribution and Warehousing Systems

Chair: Manuel Rossetti (University of Arkansas)

Simulating Inventory Systems with Forecast Based Policy Updating
Manuel Rossetti, Vijith Varghese, Mehmet Miman, and Edward Pohl (University of Arkansas)

This paper presents an object oriented framework that facilitates modeling inventory systems whose policy updating is driven by forecast estimates. In an inventory system, the forecast estimates and the forecast error measures are used to set the inventory policy. A simulation approach can address questions regarding the choice of the forecasting technique and the frequency of updating the policy, especially in non-stationary demand scenarios. This paper discusses how the framework can be used to develop simulation models through which these questions can be addressed. In addition, two examples illustrate how to use the framework and how to analyze supply chains with forecast based policy updating.

A Simulation Approach to Evaluate the Impact of Introducing RFID Technologies in a Three-Level Supply Chain
Aysegul Sarac, Nabil Absi, and Stéphane Dauzere-Peres (Ecole des Mines de Saint-Etienne)

The aim of this paper is to analyze the impacts of RFID technologies on supply chain performances, in particular to evaluate their economical impacts and to conduct ROI (Return-On-Investment) analyses. We simulate a three-level supply chain in which thefts, misplacements and unavailable items for sale cause inventory inaccuracies that decrease the supply chain performance. We compare the effects of different RFID technologies and with different tagging levels for different product types. The main originality of our research is that we are considering that there are various possible RFID systems of different costs and potential profits. The results indicate that different technologies can improve the supply chain performance at different ratios. The economical impacts depend on the chosen technology, the tagging level and the product. Our analyses thus show that the ROI of RFID applications strongly depends on the settings.

A Simulation Based Approach for Dock Allocation in a Food Distribution Center
Balagopal Gopakumar, Suvarna Sundaram, and Shengyong Wang (State University of New York at Binghamton), Sumit Koli (Maines Paper and Food Service) and Krishnaswami Srihari (State University of New York at Binghamton)

This research endeavor focused on the warehouse receiving process at a large food distribution center, which comprises of trucks with goods reaching the destination warehouse, unloading and finally putting away the contents to the specific aisles. Discrete event simulation was used to model the current system's functioning and to identify operational inefficiencies which were quantified through a detailed value stream mapping exercise. Inspired by 'lean' philosophy, a dock allocation algorithm was designed to take into account the relationship between the dock location and the destination aisle to 'optimally' assign the trucks to the docks. After validating the baseline, new scenarios incorporating the allocation algorithm were tested. Two of the scenarios showed an average reduction of 30% in daily travel distance for the 'put-away' personnel. The simulation model also helped visualize the benefits that would accrue through the use of lean principles to reduce the non-value added time in warehouse operations.

Wednesday 10:30:00 AM 12:00:00 PM
Transportation and Traffic Planning

Chair: Ralf Sprenger (University of Hagen)

Determination of Operating Policies for a Barge Transportation System through Simulation and Optimization Modeling
Gerald W. Evans (University of Louisville) and Nicholas P. Anderson (Mesoscale Diagnostics)

This paper presents a simulation model of a barge transportation system for petroleum delivery within an inland waterway. The simulation is employed as an evaluation model within a decision support system which also includes a criterion model, represented as a decision maker’s utility function, and an optimization procedure which employs scatter search. Variance reduction techniques are also employed in order to improve the accuracy of the estimates of the performance measures associated with the system. The main purpose of the system is to determine values for important inventory policy variables.

Proposed Methodology for a Data-Driven Simulation for Estimating Performance Measures along Signalized Arterials in Real-Time
Dwayne Henclewood, Michael Hunter, and Richard Fujimoto (Georgia Institute of Technology)

Congestion is one of the major issues facing today’s transportation sector. Recent efforts have been geared toward providing traffic information to travelers, to facilitate better travel decisions, and transportation facility managers, to allow them to better manage traffic operations. Currently, real-time traffic information is primarily limited to freeways and a small subset of major arterials. This research effort explores the feasibility of an online data-driven simulation based methodology to address the lack of real-time arterial performance measures. The core of this methodology is the development of an online simulation tool that relies on commonly available arterial point sensor data, such as that from loop detectors or video cameras. Preliminary analysis indicates that the approach being considered is feasible as a model of the “real-world” was capable of reflecting performance measures with relatively high levels of accuracy. Limitations of the current research design and more immediate future directions are also presented.

A Simulation Framework for Assessing the Performance of Cooperative Transportation Planning Algorithms
Ralf Sprenger and Lars Moench (University of Hagen)

In this paper, we suggest a framework that allows for the simulation-based performance assessment of algorithms for cooperative transportation planning. Therefore, we consider a coupling architecture that connects simulation models of the logistic system and the transportation planning algorithms. The center point of this architecture is a blackboard-type data layer between transportation planning system and the simulation engine. We provide detailed information on how the different subsystems communicate and how each system triggers events of the other systems. In a case study, we show how the suggested framework supports the required performance assessment.