Distributing decision making using Java simulation across the World Wide Web

This paper describes a prototype distributed, multi-user Internet based simulation environment, written in Java, and its application to decision making. An example of its use is presented in the context of manufacturing. The motivating factor behind this work is the rapid development in computer controlled plants and systems, such as automated production lines. The growth in flexibility offered by computer control has led to increasing speed and complexity in scheduling of these systems. Making such decisions often requires the very high costs of moving expert modellers and Operational Research staff to factory sites. Following developments in computer supported concurrent working (CSCW) and concurrent engineering, it is suggested that a means for working in a geographically distributed manner is desirable. The availability of Internet based solutions, exploiting Java's distributed client server architecture makes it possible to prototype such ideas in a generally accessible manner. An environment built along those lines is described here. Its benefits are shown through a case study and ideas for future work are explored.     

Bank-office Process Management in the Financial Services: a Simulation Approach Using a Model Generator

For the last ten years or so, developments in simulation software and methodology have been focused in two areas: (1) automating the model-building process; and (2) interfacing with other techniques and systems. That both academic and commercial research continues to be carried out in these areas is evidence of the continued popularity of the simulation technique. The most popular application areas where simulation modelling is used include manufacturing (engineering and process), warehousing and communications; not surprisingly, research and developments have therefore been concentrated in these areas. This paper describes the development of a simulation model generator for a different application area, that of clerical office processing of paper and documents for financial service companies. It outlines the reasons why there is a need for such a model generator and discusses the initial design requirements. The paper goes on to detail the developments and re-defined criteria required as the model generator brief changes as a result of practical applications.     

Using Simulation in Capacity Planning

This paper describes a case study concerning the application of simulation to manufacturing capacity planning. Visual interactive models were developed and used to investigate the manufacturing strategy for a particular organization. However, there are several practical difficulties which may arise in using these techniques to support managerial decisions. One of these concerns the meaning of the term ‘manufacturing capacity’. This problem was overcome by using a visual interactive version of an established procedure to complement the use of a simulation model.     

A generic model for simulating office process flows

In the field of simulation, the use of application-specific software can bring many benefits to the model-builder in terms of improved productivity and reduced skill requirements. Such software must have at its core a robust generic model for the application area which offers both the generality and sufficient detail to be able to simulate realistically. To develop such a core model, a thorough understanding of the problem area and simulation is needed. This paper describes one design for a generic core model for the simulation of office process flows where work volumes are substantial. It forms a part of a software package called SCOPE which provides a user-interface for data capture, and generates simulation models to be run using the HOCUS simulation software. Also described is the facility for static modelling which has been developed to make further use of the captured data using conventional mathematical modelling.     

Rapid and modular prototyping-based Petri nets and distributed simulation for manufacturing systems

This paper presents an approach to simulate and implement by stepwise refinement the whole manufacturing system (MS) by means of distributed simulation. This approach is based on the use of different classes of Petri nets to model different levels of a manufacturing system. Furthermore these classes may match the abstraction levels of a high-level Petri net used to model the MS. Each level can be simulated on a processor or a cluster of processors which can communicate between themselves using a network. The main contribution is to give the opportunity to combine simulation, performance evaluation and emulation. The emulation means that a part of the system can be run in real time while the other part is simulated. Moreover based on the abstraction levels of high-level Petri nets, subsystems can be integrated step-by-step from the design stage to the implementation one, allowing inter-changeability between simulated components and real-time physical systems. This approach is achieved by defining a simulation engine which involves a local simulator, an emulator and an interface to the physical process. Criteria are defined to use an emulator or a local control software for a physical process as a logical process for the conservative distributed simulation.     

Intermediate Generality Simulation Software for Production

Simulation has long been a valuable tool in the field of production. With the current and anticipated developments in computing equipment, there is a demand for simulation software, which can be used by managers to investigate specific classes of problems. The O.R. profession should involve itself in the identification of suitable areas and the development of appropriate software. Two such areas where simulation software is being developed are discussed: production planning in a batch environment and the investigation of advanced manufacturing systems.     

Simulation Model Development Environments: A Research Prototype

The needs for automated assistance in the simulation task are undeniable. The size and complexity of current modelling efforts far exceed the bounds considered challenging only a decade ago. A research prototype of a simulation model development environment (SMDE) has been developed to provide an integrated and comprehensive collection of computer-based tools to (1) offer cost-effective, integrated and automated support of model development throughout its entire life cycle, (2) improve the model quality by effectively assisting in the quality assurance of the model, (3) significantly increase the efficiency and productivity of the project team, and (4) substantially decrease the model development time. The prototype SMDE is composed of four layers: (0) hardware and operating system, (1) kernel SMDE, (2) minimal SMDE, and (3) SMDEs. Currently, a SUN 3/160 colour computer workstation and the UNIX operating system constitute layer 0, upon which an advanced prototype SMDE is being developed. The objectives of this paper are to: (1) describe the current state of research on simulation support environments; (2) use the SMDE research prototype as an example for describing concepts and principles employed, experiences gained, and guidelines (potential principles) derived in the design and creation of the prototype; and (3) identify and speculate on future research directions.     

Forty years of discrete-event simulation—a personal reflection

Discrete-event simulation first emerged in the late 1950s and it has grown in popularity steadily to be now recognized as the most frequently used of the classical Operational Research techniques across a range of industries—manufacturing, travel, finance, health and beyond. I have been engaged with such simulation from 1964 up to the present day. This paper reviews the history and evolution of discrete-event simulation from his personal perspective, with a particular interest in software development up to 1992. Extrapolating from that history, the paper goes on to comment on the prospective continuing evolution of simulation and its software.     

Effects of product postponement on the distribution network: a case study

This case study is based on a supply network analysis conducted at 3M Company, a large multi-national company headquartered in Maplewood, Minnesota. The company has developed product colouring technology that enables product postponement. This study focuses on the development of a discrete-event simulation model and inventory management equations to accurately portray the behaviour of the proposed distribution network that supports product postponement capability. The paper describes, in detail, the modelling process in the context of this actual case study. In this study, it is shown that properly devised product postponement strategy allows for best-in-class delivery within a specified lead-time. The reasons for choosing this inventory management practice are discussed. The benefits and drawbacks of product postponement are reviewed in general terms. Simulation as a tool for analysing supply networks is developed and evaluated for its ability to support a data-driven decision process.     

Comparison of some AI and statistical classification methods for a marketing case

Recent progress in data processing technology has made the accumulation and systematic organization of large volumes of data a routine activity. As a result of these developments, there is an increasing need for data-based or data-driven methods of model development. This paper describes data-driven classification methods and shows that the automatic development and refinement of decision support models is now possible when the machine is given a large (or sometimes even a small) amount of observations that express instances of a certain task domain. The classifier obtained may be used to build a decision support system, to refine or update an existing system and to understand or improve a decision-making process. The described AI classification methods are compared with statistical classification methods for a marketing application. They can act as a basis for data-driven decision support systems that have two basic components: an automated knowledge module and an advice module or, in different terms, an automated knowledge acquisition/retrieval module and a knowledge processing module. When these modules are integrated or linked, a decision support system can be created which enables an organization to make better-quality decisions, with reduced variance, probably using fewer people.     

Solving the AGV Problem via a Self-Organizing Neural Network

Automated Guided Vehicle (AGV)-based material handling systems (MHS) are used widely in Flexible Manufacturing Systems (FMS). The problem of AGV consists of the decisions and the operational control strategies of dispatching, routeing and scheduling of a set of AGVs under given system environments and operational objectives. One remaining challenge is to develop effective methods of AGV decisions for improved system productivity. This paper describes a prototype neural network approach for the AGV problem in an FMS environment. A group of neural network models are proposed to perform dispatching and routeing tasks for the AGV under conditions of single or multiple vehicles, and with or without time windows. The goal is to satisfy the transport requests in the shortest time and in a non-conflicting manner, subject to the global manufacturing objectives. Based on Kohonen's self-organizing feature maps, we have developed efficient algorithms for the AGVs decisions, and simulation results have been very encouraging.     

Modelling a Solid-Waste Processing System by Discrete Event Simulation

This paper describes a discrete event simulation model for a solid-waste processing system which is to be installed in Zagreb, Croatia. The conceptual model was developed by activity cycle diagrams, and the computer model was developed using the program generation software package VS6. This paper describes the validation and verification of such a model, the design of simulation experiments and the selection of the system's configuration.     

Application of Computer Simulation to Freight Transport Systems

Selecting an appropriate simulation-model structure for complicated, large-scale transport systems is a non-trivial and challenging task. This paper reports practical research which evaluates a number of alternative model structures for the Arizona state-highway network system based on the immediate dependency on input data obtained from a multistage mail survey. The most appropriate topology structure selected is a data-driven, link-based, discrete-event simulation model using conditional probability branching logic. Separating model and data makes the simulation model a generic traffic-routeing logic processor that is easy to use and does not require simulation skills. Different transport systems can easily be accommodated by simply changing input data. The model is validated by comparative analysis of input data using statistical techniques. An upper bound on the size of the valid network is thus obtained.     

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance.     

Artificial Intelligence Approaches to Simulation

Recent years have seen a number of attempts to apply both AI methods and AI software tools to the development of both simulations and simulation packages. This paper discusses the motivation behind such work: the increasing need for AI researchers to include simulation in AI systems and use simulation in research, and the need to model intelligent behaviour in OR simulation models. The current research and development effort is reviewed. A system called PROSS (the PROlog Simulation System), constructed to allow the integration of AI methods with traditional discrete simulation, is then briefly presented. It is concluded that AI software tools, and some of the novel approaches to simulation being taken by AI researchers, will have a considerable impact on simulation.     

A simulation model for emergency evacuation

This paper describes the development of a prototype spatial decision support system for use by emergency planners in developing contingency plans for evacuations from disaster areas. It links together a geographical information system (ARC/INFO) with a specially written object-oriented micro-simulator via a windowing computer operating system. The details of the system are described, its limitations are discussed and potential enhancements are identified.     

Parallel Finite Element Software Development and Performance Analysis in an Object-Oriented Programming Framework

The use of object-oriented programming techniques in the development of parallel, finite element analysis software enhances code reuse and increases efficiency during application development. In this paper, an object-oriented programming framework developed by the authors is utilized in the implementation of parallel finite element software for modeling of the resin transfer molding manufacturing process. The motivation for choosing the resin transfer molding finite element application and implementing it with the object-oriented framework is that it was originally developed and parallelized in a functional programming paradigm thus offering the possibility of direct comparisons. Discussion of the software development effort and performance results are presented and analyzed.Mathematics Subject Classifications (2000) 65M60, 65Y05.     

FMS scheduling as cooperative problem solving

This paper describes an FMS scheduling method that treats an FMS as a group of problem-solving agents cooperating to perform manufacturing jobs. The main thrusts of such a method include the ability to handle the dynamically changing production conditions, its taking into account the communication method, the improved reliability, and the use of distributed control. The paper emphasizes research issues associated with various aspects of the cooperative problem-solving method, including: (1) dynamic task assignments, (2) the coordination mechanism, and (3) knowledge-based scheduling as problem solving. A simulation study which compares the performance of the cooperative problem solving approach with that of the more traditional scheduling approaches is also reported.