A VARIANCE-REDUCTION STRATEGY FOR RSM SIMULATION STUDIES

The application of optimization techniques in digital simulation experiments is frequently complicated by the presence of large experimental error variances. Two of the more widely accepted design strategies for the resolution of this problem include the assignment of common pseudorandom number streams and the assignment of antithetic pseudorandom number streams to the experimental points. When considered separately, however, each of these variance-reduction procedures has rather restrictive limitations. This paper examines the simultaneous use of these two techniques as a variance-reduction strategy in response surface methodology (RSM) analysis of simulation models. A simulation of an inventory system is used to illustrate the application and benefits of this assignment procedure, as well as the basic components of an RSM analysis.     

A simulation system for corporate planning

This paper describes the structure and use of a general purpose simulation package developed for the interactive construction of dynamic computer-based simulation models. The package consists of a system of computer programs written in the BASIC language for a Digital PDP 11/70 time-sharing computer.The framework upon which the package is based is essentially an amalgamation of the System Dynamics and Input-Output approaches to the modelling of complex organizations. Networks of levels and flows provide the basis for dynamic, modular representation, while matrix algebra features provide the basis for aggregational flexibility and the analysis of multi- product multi-process industrial systems.The package is designed to provide planning managers with the ability to construct flexible models, localized or ‘corporate’, financial or non-financial, without the need for any programming in the conventional sense. A flow diagram of the system to be modelled guides the model builder in responding to computer terminal prompts which determine the model structure as a set of programmed relationships. This in turn gives rise to a further series of prompts at the terminal for the entry of all data pertinent to the model. Model editing and computation then proceeds, with user interaction, if desired, for amendments, monitoring of computations, and report generation.Two specific applications of the package are discussed in the latter part of the paper, and sample output from runs of both of the resultant models is provided.     

A Monte Carlo Procedure for the Construction of Complementary Cumulative Distribution Functions for Comparison with the EPA Release Limits for Radioactive Waste Disposal

A Monte Carlo procedure for the construction of complementary cumulative distribution functions (CCDFs) for comparison with the U.S. Environmental Protection Agency (EPA) release limits for radioactive waste disposal (40 CFR 191, Subpart B) is described and illustrated with results from a recent performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP). The Monte Carlo procedure produces CCDF estimates similar to those obtained with importance sampling in several recent PAs for the WIPP. The advantages of the Monte Carlo procedure over importance sampling include increased resolution in the calculation of probabilities for complex scenarios involving drilling intrusions and better use of the necessarily limited number of mechanistic calculations that underlie CCDF construction.     

产业集群参与者交互偏好与知识网络演化:模型与仿真

知识网络是产业集群网络演化的重要组成部分和先决条件,本文将产业集群中参与者进行交互的偏好分为任务导向型和知识导向型,建立了一个基于多智能主体的产业集群知识网络模型,利用Blanche软件实现了知识网络演化模型的仿真计算,通过仿真研究了任务导向型和知识导向型知识网络的对网络演化的不同影响.最后,本文提出了研究的局限性和下一步研究的方向.     

Reducing Surgical Ward Congestion Through Improved Surgical Scheduling and Uncapacitated Simulation

High surgical bed occupancy levels often result in heightened staff stress, frequent surgical cancellations, and long surgical wait times. This congestion is in part attributable to surgical scheduling practices, which often focus on the efficient use of operating rooms but ignore resulting downstream bed utilization. This paper describes a transparent and portable approach to improve scheduling practices, which combines a Monte Carlo simulation model and a mixed integer programming (MIP) model. For a specified surgical schedule, the simulation samples from historical case records and predicts bed requirements assuming no resource constraints. The MIP model complements the simulation model by scheduling both surgeon blocks and patient types to reduce peak bed occupancies. Scheduling guidelines were developed from the optimized schedules to provide surgical planners with a simple and implementable alternative to the MIP model. This approach has been tested and delivered to planners in a health authority in British Columbia, Canada. The models have been used to propose new surgical schedules and to evaluate the impact of proposed system changes on ward congestion.     

Simulation optimization through direct search for multi-objective manufacturing systems

Simulation modelling has been one of the most widely used techniques for analysing complex manufacturing systems. In this paper, we propose a direct search algorithm expanded from the Hooke-Jecves pattern search to systematically and efficiently locate satisfactory solutions for multi-objective simulation models. The user-specified goals can be precise and/or fuzzy. Heuristic rules stemming from the simulation result of resource statistics are incorporated into the Hooke-Jeeves pattern search. The proposed heuristic rules make the search procedure effective regardless of different initial points and various bounded ranges of decision variables. Experimental results show that the proposed approach is suitable for analysing complex manufacturing systems, in which multiple objectives and multiple decision variables are encountered.     

SIMULATION FOR FIRE DEPARTMENT DEPLOYMENT POLICY ANALYSIS

This paper discusses the use of simulation in the determination and analysis of alternative deployment strategies for urban fire supression systems. The simulation model utilizes the New York City-Rand Institute simulator of fire department operations tailored for use with the Denver Fire department. A distinction is made between static deployment (where mathematical programming methods are used) and dynamic analysis (which employs the simulation model). The simulation model is described, as are its extensive data requirements. The results discuss measures of validation of the simulation and outline the recommendations resulting from this research.     

Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases

A novel approach to the quantitative assessment of food-borne risks is proposed. The basic idea is to use Bayesian techniques in two distinct steps: first by constructing a stochastic core model via a Bayesian network based on expert knowledge, and second, using the data available to improve this knowledge. Unlike the Monte Carlo simulation approach as commonly used in quantitative assessment of food-borne risks where data sets are used independently in each module, our consistent procedure incorporates information conveyed by data throughout the chain. It allows "back-calculation" in the food chain model, together with the use of data obtained "downstream" in the food chain. Moreover, the expert knowledge is introduced more simply and consistently than with classical statistical methods. Other advantages of this approach include the clear framework of an iterative learning process, considerable flexibility enabling the use of heterogeneous data, and a justified method to explore the effects of variability and uncertainty. As an illustration, we present an estimation of the probability of contracting a campylobacteriosis as a result of broiler contamination, from the standpoint of quantitative risk assessment. Although the model thus constructed is oversimplified, it clarifies the principles and properties of the method proposed, which demonstrates its ability to deal with quite complex situations and provides a useful basis for further discussions with different experts in the food chain.     

Job sequencing to minimize tool changeovers in flexible manufacturing systems

The combination of group technology and heuristic is used to schedule jobs on a machine equipped with an automatic tool changer (ATC). The problem is prominent in flexible manufacturing systems where the efficiency in operation is, in part, obtained by use of ATC. The procedure presented here is efficient and does not require complex mathematics.     

Step-through simulation

This report describes the initial development of the Step-Through variant of Monte Carlo simulation, a new procedure for implementing decision analysis or for training decision makers. Like regular Monte Carlo simulation, it involves sampling possible aftermaths of an initial action, and generating a distribution of outcome values for it. However, the detailed structure and/or assessments of the decision model are elicited as called for in the execution of each trial. It, therefore, permits substantial economy of elicitation if there are few trials. The Step-Through procedure also offers economy of elicitation and calculation over a traditional extensive tree decision-analytic model without requiring simplifications or aggregations in the model's conceptualization. In addition to describing this procedure, this paper presents the results of a preliminary test and evaluation of its viability.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

DYNAMIC LOT SIZING FOR A SINGLE-FACILITY MULTIPRODUCT PROBLEM IN A ROLLING-HORIZON ENVIRONMENT

This paper considers a production planning model for a single-facility multiproduct problem where backlogging is not allowed. A planning-horizon theorem is derived. From that theorem, a forward algorithm for finding an optimal solution over a finite horizon and a procedure for selecting the first-period production in a rolling-horizon environment are developed. Computational results from a set of simulation experiments designed to investigate the cost effectiveness of the procedure demonstrate its effectiveness.     

Using simulation to illuminate process improvement opportunities in a U.S. naval aircraft overhaul facility

Fleet Readiness Center Southwest (FRC SW) is the largest aerospace industrial complex in the U.S. Navy. The FRC SW conducts maintenance, repair and overhaul (MRO) activities on five major airframes with many of them being more than 20 years old. With demand for the aircraft in the field high, management at FRC SW were under enormous pressure to shorten the turn-around times of aircraft – the time between an aircraft being inducted for overhaul and the time it was returned to the warfighter for use in active military operations. Leadership at FRC SW requested the development of a simulation model that would incorporate all the important aspects of the complex and variable operating environment of their MRO facility and lend insight into how various factors and changes could affect the throughput time of aircraft across the facility. This research describes how the development and use of a simulation model uncovered several significant opportunities for management at FRC SW to increase turn-around time. The model also illuminated where simple policy changes could eliminate the need for additional capital investments, and where additional capital was needed the model indicated where it would yield the greatest return.     

供应链产品物流过程模型及时间瓶颈的识别

供应链时间瓶颈的识别是对供应链进行时间压缩的首要环节.本文首先根据供应链网状模型和无边界集成的供应链合作思想,将供应链中产品生产过程看作是一个物在供应链各环节的流动过程.在对这一物流过程进行分析的基础上建立了供应链产品的物流过程模型,并使用产品物流在供应链各环节流动的转移概率,结合价值工程的思想,提出了基于产品物流过程转移概率的供应链时间瓶颈识别方法,给出了供应链时间瓶颈识别与压缩的方法和流程,最后使用算例进行了仿真研究.     

Simulation-based performance assessment of master planning approaches in semiconductor manufacturing

Semiconductor manufacturing is confronted with a large number of products whose mix is changing over time, heterogeneous fabrication processes, re-entrant flows of material, and different sources of environmental and system uncertainty. In this context, the mid-term production planning approach, i.e., master planning, typically does not capture the entire complexity of the shop-floor. It deals with an aggregated representation of the production system. There is a need for evaluating the planning algorithm in use while taking the execution level into account. Therefore, we introduce in this paper a simulation-based framework that allows for modeling the behavior of the market demand and the production system. An appropriate performance assessment methodology is proposed. The performance of two heuristic approaches for master planning in semiconductor manufacturing, a genetic algorithm and a rule-based assignment procedure, is evaluated within a rolling horizon setting while considering demand and execution uncertainty. A reduced discrete-event simulation model is used to mimic a one-stage network of wafer fabrication facilities. The results of simulation experiments are discussed.     

The application of filter theory to the study of supply chain dynamics

Recently, there has been a rebirth of interest in supply chain demand amplification, a trend accelerated by the availability of a wide range of simulation packages. However, although this approach provides some guidance on design improvements possible in a given situation, it rarely offers insight for the future. In the present paper the use of simple filter theory is proposed to help bridge this gap. The example chosen to illustrate the approach is a three-echelon system in which there are factory, distributor, and retailer activities. The results vividly confirm an optimal design previously obtained via a multi-attribute utility technique (MAUT) expert system. However, the knowledge gained via filter theory should improve yet further the effectiveness of the expert system. This is because the sequential steps to be followed when varying the echelon dynamics as part of the search procedure can be greatly improved. The paper concludes by showing how simulation results might be used to confirm the supply chain dynamic design which will minimize stockholdings in the presence of demand fluctuations. However, it should be noted that in common with the successful application of systems dynamics techniques in production-distribution systems generally, the solutions are most applicable to the medium-term operations horizon. The latter term may need re-definition for use in ‘lean’ supply chains. Our intuitive reaction is that a scientific definition may well turn out to be a multiple of the largest remaining process lead-time in the slimmed down supply chain rather than being the customary arbitrary choice of, for instance, a 12-month period.     

Influence of Safety Measures on the Risks of Transporting Dangerous Goods Through Road Tunnels

Quantitative risk assessment (QRA) models are used to estimate the risks of transporting dangerous goods and to assess the merits of introducing alternative risk reduction measures for different transportation scenarios and assumptions. A comprehensive QRA model recently was developed in Europe for application to road tunnels. This model can assess the merits of a limited number of "native safety measures." In this article, we introduce a procedure for extending its scope to include the treatment of a number of important "nonnative safety measures" of interest to tunnel operators and decisionmakers. Nonnative safety measures were not included in the original model specification. The suggested procedure makes use of expert judgment and Monte Carlo simulation methods to model uncertainty in the revised risk estimates. The results of a case study application are presented that involve the risks of transporting a given volume of flammable liquid through a 10-km road tunnel.     

基于并行工程的企业资源计划过程建模

在论述了企业资源计划以及基于并行工程的企业资源计划 (CE- ERP)的基础上 ,描述了 CE- ERP过程模型结构 ,重点分析了其任务对象企业供应链 ,采用全局协调与局部仿真相结合的方法建立企业供应链的模型 ,最后说明了模型的应用和优越性     

AN EVALUATION OF SEQUENCING RULES FOR AN ASSEMBLY SHOP

Research relating to sequencing rules in simple job shops has proliferated, but there has not been a corresponding proliferation of research evaluating similar sequencing rules in more complex assembly job shops. In a simple job shop, all operations are performed serially; but an assembly shop encompasses both serial and parallel operations. As a result of the increased complexity of assembly shops, the results associated with the performance of sequencing rules in simple job shops cannot be expected for an assembly shop. In this paper, 11 sequencing rules (some of which are common to simple job shops and some decigned specifically for assembly shops) are evaluated using a simulation analysis of a hypothetical assembly shop. The simulation results are analyzed using an ANOVA procedure that identifies significant differences in the results of several performance measures. Sensitivity analysis also is performed to determine the effect of job structure on the performance of the sequencing rules.     

AGGREGATING EXPERT OPINION IN DECISION-MAKING

In using nominal groups for decision making, it is necessary to use some mechanical procedure for combining the evaluations. A simulation model is used to compare procedures for the case where a nominal group of m evaluators must select the best of n alternatives and where the evaluations are subject to random errors. Criteria are the probability of making a correct selection and the relative quality of the choice.