Object-orientation,Discrete Simulation and the Three-Phase Approach

The three-phase approach provides a simple and robust way to develop discrete computer simulation programs. Object-orientation allows system developers to develop software which can be extended and also makes it impossible for important variables within a software system to be tampered with. This paper shows how the two approaches can be usefully combined and discusses the development of a simulation library, written in C++ and based on these ideas. Limitations of both approaches are also discussed.     

A Discrete Event Simulation of Sugar Cane Harvesting Operations

Sugar cane harvesting consists of the following operations: cutting the cane, carrying it from the field to the processing plant and unloading it there. Before being harvested, the sugar cane is burnt and after burning it has to be processed within 15 days, otherwise the saccharose in it will gradually transform into ethylic alcohol and the cane will have to be discarded, because sugar cannot be extracted from it. In this paper, we present a simulation algorithm for scheduling the operations and for planning the resources available, in such a way that the time between the end of cane burning and the start of processing is minimized. This algorithm can provide the basis of a decision support system for minimizing the quantity of discarded cane and optimizing the utilization of resources.     

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.     

The Role of Discrete Event Simulation Techniques in Finite Capacity Scheduling

Discrete event simulation is becoming an established tool in finite capacity scheduling. However, recent work on scheduling systems has concentrated on the development of different modelling approaches and tools, without proper examination of how they can be used to meet business objectives. This paper examines the role of scheduling in improving business performance and suggests possible considerations in the development and implementation of a finite capacity scheduler. It reviews the advantages and limitations of discrete event simulation as a modelling technique for scheduling, and argues the need for further research to develop more versatile tools. A simulation-based scheduling system incorporating bottleneck planning principles to maintain throughput with low inventory is described, as are the experiences gained during its implementation in a medium-sized press shop.     

Introduction to the Special Issue on Discrete Event Models of Continuous Systems

Automatic control systems rely on models to predict the near future and identification algorithms to adapt the models to changing process behaviour. The traditionally highly complex models of the activated sludge process developed for scientific purposes cannot be identified from on-line measurements and are not suited for process control purposes in their present form. Model decoupling based on the different time scales of the dynamic processes is one possible way of attacking this problem. It allows the implementation of more simple and realistically applicable controllers in combination with predictions based on simplified models in hierarchical control structure. This paper discusses these concepts and presents a reduced order model describing carbonaceous removal, nitrification, and denitrification in a medium time scale (several hours/days). The model parameters are identifiable from available on-line measurements and the dynamic behaviour is verified against computer simulations of the IAWQ activated sludge model no. 1.     

具有年龄结构的离散HIV/AIDS模型的全局分析

本文根据艾滋病传播的特点建立了有年龄结构的高维离散SIA模型,和有干预的具有年龄结构的离散HIV模型.对每种模型,我们首先给出了建模思想,用差分方程建立了数学模型,然后对模型平衡点的稳定性进行了理论分析,得出一定条件下模型无病平衡点和地方病平衡点的稳定性.另外,本文还给出了模型的基本再生数,其意义为一个病人在染病期内平均感染的人数,基本再生数决定了模型无病平衡点和地方病平衡点的存在性和稳定性.     

基于离散事件仿真的妇产科孕妇建卡接收规则优化

孕妇在怀孕九周后会选择一家医院申请建立孕妇档案卡(简称建大卡),管理者需决定是否接收。一旦该医院做出接收决策,孕妇将在该院接受妊娠期内的产检并在该医院分娩。孕妇在妊娠期内所需的医疗资源的多样化、尤其是对关键资源即病床需求时间及服务时间不确定性,增加了决策的难度,从而导致妇产科资源利用率分布不均衡,影响医疗服务质量。为了解决该问题,本文首先建立动态规划模型来最小化病床的空闲、加床和转院的惩罚成本。由于动态规划模型非常复杂,难以用解析方法来获取最优控制策略,因此本文建立离散事件仿真系统,以病床的空闲、加床和转院的惩罚成本最小化为目标,采用广域搜索对多种阈值控制策略进行参数优化。数值实验表明,本文提出的阈值策略比医院目前采用的阈值策略有显著改进,进一步进行了敏感度分析,发现随着到达率逐渐增大,期望成本首先逐渐降低然后在某一水平上波动,加床成本的上升对于期望成本的影响更大。     

模糊离散事件动态系统及模糊数输入法仿真技术

本文以时间论域上的模糊集为基本模糊事件，定义了模糊离散事件动态系统，给出了系统的数学模型，以ＦＭ／ＦＭ／１排队系统为例，演示了模糊数输入法仿真技术，给出了有关结果，为管理系统仿真应用模糊集理论提出了一条新的途径。     

A Three-Phase Simulation System Written in Pascal

A three-phase simulation system written in Pascal for use on microcomputers, minis and mainframes is presented. The advantages of the three-phase method are discussed, and the basis of the system explained. Although a traditional, textbook example is used to aid explanation and discussion, the system described in this paper has been used in real applications and in the teaching of simulation at Lancaster University and the London School of Economics. It also provides a basis for further research in simulation within both institutions.     

Markov Property in Discrete Schur-constant Models

This paper is concerned with Schur-constant survival models for discrete random variables. Our main purpose is to prove that the associated partial sum process is a non-homogeneous Markov chain. This is shown in three different situations where the random variables considered take values in the sets ₀, {0,1} or {0,…,m}, m ≥ 2. The property of Schur-constancy is also compared for these three cases.     

Mathematical Models of Discrete Self-Similarity

Natural phenomena which exhibit discrete self-similarity are under consideration. Earlier, self-similarity of some non-smooth phenomena was studied using the concept of log-periodicity, however there was a gap in this field. Recently it was attempted to fill this gap by concentrating on the study of a new concept of parametric-homogeneity (PH) based on the use of discrete group of coordinate dilations. It is argued that parametric-homogeneity can be helpful in the modelling of self-similar non-smooth phenomena. Some models of natural phenomena which have PH-features are presented and some properties of PH-functions are discussed. As an example of practical usage of these functions, the phenomenon of seismic activation prior to a major earthquake is considered.     

Combining Data Mining and Discrete Event Simulation for a value-added view of a hospital emergency department

While simulation models have furthered understanding of the operations of emergency departments (EDs) and the dynamics of the ED within the healthcare system, they only model patient treatment implicitly, tracing the paths patients follow through the ED. By identifying the core patient treatments provided by the ED and incorporating them into a Discrete Event Simulation model, this paper provides insight into the complex relationship between patient urgency, treatment and disposal, and the occurrence of queues for treatment. The essential characteristics of the presented model are used to indicate a generally applicable methodology for identifying bottlenecks in the interface between an ED and a hospital ward.     

Wegner Estimate for Discrete Alloy-type Models

We study discrete alloy-type random Schrödinger operators on ${\ell^2(\mathbb{Z}^d)}We study discrete alloy-type random Schr?dinger operators on l²(\mathbbZ^d){\ell^2(\mathbb{Z}^d)} . Wegner estimates are bounds on the average number of eigenvalues in an energy interval of finite box restrictions of these types of operators. If the single site potential is compactly supported and the distribution of the coupling constant is of bounded variation a Wegner estimate holds. The bound is polynomial in the volume of the box and thus applicable as an ingredient for a localisation proof via multiscale analysis.     

A Event Occurrence Rules based Compact Modeling Formalism for a Class of Discrete Event Systems

The analysis, failure diagnosis and control of discrete event systems (DESs) requires an accurate model of the system. In this paper we present a methodology which makes the task of modeling DESs considerably less cumbersome, less error prone, and more user-friendly than it usually is. In doing so we simplify the modeling formalism of [4, 5], proposed for obtaining valid models of complex discrete event systems, by eliminating ‘precedence relations’, and capturing them as part of the ‘event occurrence rules’. Under the new modeling formalism the size of the system model is polynomial in the number of signals; whereas the number of states in the commonly used automata models is exponential in the number of signals. We present automated techniques for deriving an automaton model from the model in the proposed formalism. We illustrate the modeling formalism using examples drawn from manufacturing and process control systems.     

Convex Models of High Dimensional Discrete Data

Categorical data of high (but finite) dimensionality generate sparsely populated J-way contingency tables because of finite sample sizes. A model representing such data by a "smooth" low dimensional parametric structure using a "natural" metric would be useful. We discuss a model using a metric determined by convex sets to represent moments of a discrete distribution to order J. The model is shown, from theorems on convex polytopes, to depend only on the linear space spanned by the convex set—it is otherwise measure invariant. We provide an empirical example to illustrate the maximum likelihood estimation of parameters of a particular statistical application (Grade of Membership analysis) of such a model.