This paper describes a System Dynamics model of the foreign trade sector in a small open economy. The model is used to investigate the consequences of various economic policies aimed at solving problems which a high-cost country may experience when its debt-ratio begins to increase. With the model, we simulate some of the economic consequences of currency devaluation, tax increase, restrictive public policy and income freeze. Each of these measures significantly improve the debt-ratio, but only after a delay of 5-8 years, as a result of various bottlenecks in the decision-making process.
The paper is organized in three parts. It begins with a brief review of the substantive exchange of views in the case, including the Company’s position, the Attorney General’s position, and the analyses and counter analyses presented in support of these positions. In Part Two, the paper describes the participants and the schedule of the hearings. It is argued that the rapid pace of these hearings and the background of the participants are important determinants of usefulness of System Dynamics models under adversary proceedings. The third part of the paper concludes with a discussion of the advantages and disadvantages of system dynamics under fast paced, adversary conditions.
The aggregate demand-aggregate supply (AD-AS) model presented in most intermediate and advanced macroeconomic texts may provide misleading insights into the effects of economic stabilization policies. Conventional analysis of the AD-AS model shows that policies which raise demand during periods of peak unemployment and reduce demand during periods of low unemployment tend to stabilize the economy. This paper: (1) Develops a dynamic model of the AD-AS model; (2) Shows that the model produces a very long period of oscillation (approximately 50 years); (3) Shows that the conventional stabilization policies increase damping of the long cycle; (4) Adds inventories to the base model; (5) Shows that the inventories introduce a business cycle fluctuation to model behavior; (6) Shows that the conventional stabilization policies destabilize the business cycle behavior mode. This paper should help explain why standard “stabilization” policies tend to destabilize the business cycle in the System Dynamics National Model.
The Causal Loop Diagram, a signed diagraph which shows the variables and interactions of a system Dynamic model, has been studied. It has been found convenient to start with the levels and their interactions. Then signed interactions between levels and rates may proceed. The transformation from signed level diagraph into Causal Loops, in terms of levels and rated, is presented. Dynamics properties such as stability, oscillations, controllability, and observability are related to the information contained in the Causal Loop Diagram. These dynamics properties have been found very useful in the synthesis of policies aimed to manipulate structure. Illustrations and examples are inserted in the exposition.
It was the purpose of this study to describe a modest theory of educational change which could be stated with some precision, which could reproduce observed historical behaviors, which could facilitate an understanding of the structural dynamics giving rise to those behaviors, and which would permit the examination of selected policies which have some historical currency.
To improve matters in the behavioral sciences, system dynamics can play the role of catalyst by providing both the holistic view which is needed to understand the behavior of human beings and not just bits and pieces of their actions and the necessary technical tools to map behavior over into manageable models. In return, system dynamicists will learn how to include a more differentiated and thus more realistic representation of human behavior in their models of social systems.
The purpose of this paper is to introduce an integrated framework for long-range strategic planning to a railroad. The framework is a computer simulation model designed to be useful to most freight –hauling railroads. The model can help to increase the understanding of problems facing the railroad and to aid in developing strategies for addressing these problems. It is designed to forecast railroad performance and to aid in developing more effective policies for railroad management. It can also be used by Federal agencies to evaluate impacts policy on railroad performance.
Since 1972, Jay Forrester and colleagues at MIT have been evolving the System Dynamics National Model (SDNM). The purpose of this model is to guide policy makers in dealing with today’s major problems. The ambitious scope of the project motivates careful examination of modeling practices and how they contribute to the success of the project. The above paper recounts incidents in the development of the SDNM and discusses the related modeling issues.
The model in this paper is, therefore, directed towards an understanding of the mechanisms at work during the UK business cycle. Its time horizon is no greater than ten years, with the main emphasis on the next five. It is frequently argued that cycles of longer period than the business cycle exist, e.g. the 50 year long wave. It is not intended that this model should try to capture in detail the mechanisms believed to produce them. However, their role in determining the underlying trend must be recognized, and their effects incorporated exogenously, perhaps by reference “off-line” to other models designed to look at these more distant horizons.
Planning and Control are essential for the success of any human endeavour and are now widely established concepts in most organizations, usually enshrined in formal corporate/planning systems. The process of planning may be analysed in a number of different ways, but generally there is a consensus on the need to split the process up into strategic planning, which directs the organization and tactical or operational planning which deals with the resource allocation for specific operational units and integrates them into the whole.
This paper explores the possible paths of emergence of a new medical technology and how those paths might be altered by government regulations of the sort now promulgated by the Food and Drug Administration (FDA). The purpose of the paper is to help clarify the role of FDA regulation in a dynamic context. The analysis focuses on the idea that an emerging technology’s effectiveness may change over time and that the benefits and losses due to regulation may themselves have a dynamic character. An increasingly complex story of the emergence (or dissemination and development) process is told with the help of causal-loop diagrams. Results from a preliminary system dynamics model based on this story are illustrated and discussed. They suggest that the FDA’s actions may have unintended effects, such as slower development of a technique, which may or may not be harmful. They also suggest that, in certain cases, post-marketing surveillance and communication of results may be at least as important an activity for the FDA as pre-marketing evaluation.
In order to investigate the regulation of breathing under various conditions, we have developed a dynamic model of the human respiratory and cardio-vascular systems. The model describes the flows of oxygen and carbon dioxide between the atmosphere and the tissues as well as the chemical regulation of breathing in a rather detailed manner. When testing the model with a step increase in muscular metabolism (simulating a transition from rest to physical activity), it reproduces clinical observations for the variation in ventilation and in arterial oxygen and carbon dioxide pressures. The model also reproduces the respiratory response to changes in the composition of the inspired air. Combined with a model of the Hafnia A anaesthetic system, the respiratory system model has finally been used to examine the life-threatening dynamical run-away effects which may occur, if the fresh gas flow is reduced too much, and the patient starts to rebreathe his own expiration.
This paper is destined not so much for those who are present at this conference than for the members of the business community whose absence constitutes one of the main problem facing System Dynamics. Indeed, since its inception more than 20 years ago, quite a few Industrial or System Dynamics publications have dealt with industry or government related applications. However, very few of those have been effectively developed within and present by business or government representatives.
Our work during the past several years leads us to believe that there now exists a small but significant number of American corporations engaged in daring experiments in organizational transformation. These companies fundamentally alter our understanding of how a group of people can work together. They are committed to the absolute highest in organizational performance and human satisfaction. They view themselves as microcosmic demonstrations of how society could work towards everyone’s fulfillment.
The SD approach is based on control theory. As with general system theories, it postulates that system structure causes system behavior. Computer simulation used to be the only means of solving complicated models at the time SD was invented. Therefore: (1) only system structure and system behavior could be used as yardsticks in model validation (2) without an intuitive or intelligent guess, that related structural explanation to model behavior, all modelling work would have been fruitless or at least extremely laborious. In computer simulation, no automatic feedback from model behavior to structural changes is feasible. A human link is needed and, therefore, system dynamists have rightly argued about the significance of insights gained from the very modelling process. Without insights, no feedback mechanism would work properly in model construction. The authoritarian relationship between man and machine, prevailing in SD, is an outgrowth of this situation.
The scientific technique known as the method of multiple hypotheses can be adapted to suit the purposes of system dynamics policy modeling. This method would allow determination of a model’s value through comparison with other competing models. It would also diminish modelers’ emotional attachment to any single theory. But in adopting this method, system dynamicists would need to develop a new philosophy of model evaluation, emphasizing disproof over verification and comparison among theories over improvement or elaboration on a single model.
This abstract describes the further development of the project “Introduction `of innovative Products into a competitive Market”, the former stages of which have been already described into the Proceedings of the 1980 International Conference on Cybernetics Society, Cambridge 1980 (Krallmann (1980)). The management of the company we cooperated with wanted to get support in the decision making process of introducing innovative but similar products into a competitive market.
The motivation for developing this model came from an academic interest in the dynamics of recreational behavior as well as in responding to passing recreational problems faced by state officials and tourist industry planners. The current energy picture and economic climate in Midwestern United States appears to be relatively bleak. Michigan, for example, whose economic life revolves around the state of the automobile industry, is reeling from sharp declines in auto sales. The cost of energy, for the most part, has been increasing over the past eight years at a phenomenal rate, not only increasing the cost of automobiles, but also affecting consumer choices and preferences for smaller and more economical cars.
The philosophy of constructing models requires that the models be sufficiently detailed in order for them to have a significant impact on the development of detailed corporate plans. Although dynamic behavior may adequately be captured by a “simple” model, our experience in preparing models for a number of corporations indicates that detail is useful to facilitate initial acceptance of the model, and is often essential in assuring the model’s continued use by the client.
The background of this paper is an analysis carried out on the occasion of an election within an academic self-administration in West Berlin in 1980/81. This analysis considers (1) papers presented during the time before the election with opposing opinions as to image and efficiency of this administration, and (2) statistical data concerning possibilities within the structure of this administration and the realization of these possibilities by members of the staff over a period of seven years.
Both in incipient and later phases of developing a model, unexpected behavior is frequently encountered—that is, behavior which is at odds with the initial expectations of the model builder or client. The appearance of such surprise behavior immediately raises two possibilities: either the behavior is implausible, and the model therefore must be revised; or the behavior withstands scrutiny and reveals previously unappreciated aspects of the system. In either instance, the process of diagnosing and interpreting surprise behavior gives a powerful basis for model for model evolution and generating policy insights. But frequently, it is quite difficult in practice to discern whether the incidence of surprise model behavior reveals errors or suggests insights. The paper is designed to contribute to the literature on model formulation, testing, and policy analysis, by discussing the criteria for diagnosing surprise model behavior. Several case examples are presented in which appropriate resolution of surprise model behavior led to significant model improvements and/or behavior insights. Moreover, operational guidelines are presented to increase the likelihood of uncovering and successfully treating surprise behavior.
A particularly interesting area for the application of system dynamics methodology is in business management; especially the interplay of quantitative (financial, economic) and qualitative factors (motivation, morale), and the decision-making choices which confront management. When a firm has a product which can be measured in economic terms, the construction of a model can be quite straight-forward. Even in non-quantitative areas such as research and development, models have provided insight into the decision-making process. While these models have been informative from both a system dynamics and management science perspective, the practical application of the results has been too often lacking. For a businessman, simulations and models are academic exercises unless they provide some measure of practical guidance. It was from a basis of requiring that the system dynamics model provide practical decision-making guidance in real-world environments that we have attempted several studies of R&D projects.
This paper examines the linkages between system dynamics and the Carnegie school in their treatment of human decision making. It is argued that the structure of system dynamics models implicitly assumes bounded rationality in decision making and that the recognition of this assumption would aid system dynamicists in model construction and in communication to other social science disciplines. The paper begins by examining Simon’s “Principles of Bounded Rationality” which draws attention to the cognitive limitations on the information gathering and processing powers of human decision makers. Forrester’s “Market Growth Model” is used to illustrate the central theme that system dynamics models are portrayals of bounded rationality. Close examination of the model reveals that the information content of decision functions is limited and that the information is processed through simple rules of thumb. In the final part of the paper there is a discussion of the implications of Carnegie philosophy for system dynamics, as it affects communication, model structuring and analysis, and future research.
This study proposes to compare two types of computer simulation techniques, namely tactical and strategic simulations. It explores the advantages and disadvantages of the two methods and stresses the importance of the insight to be gained by combining both approaches in the evaluation of public policies. A school finance reform policy is presented as a case study. More specifically, the research evaluates the implementation of a cost-of- education index (a mechanism to adjust for disparities in educational costs among school districts in a state) in the New York State aid formula. The study investigates, using two computer simulation techniques, the impact of this policy in terms of organizing per pupil expenditures.
My paper focuses on an extension of the basic R&D model. The basic model uses the concept of an average product which the firm develops and eventually sells. The extended model used in my paper diaggregates products into products and architectures. In the extended model, products are developed and sold just as they are in the basic model. An “architecture” is a basic engineering development which, when completed, enables the firm to develop a large number of products. An investment of resources in architectural development is necessary before marketable products can be created.
Many Congressional and Executive Branch policymakers are becoming discontent with the contribution of models to the policy process. One reason the modeling process and modeling results are being questioned is because of their perceived incomprehensibility and limited utility. This discontent has intensified with the Administration’s proposed reductions in domestic programs. This new mood of austerity is forcing researchers to justify modeling as useful to government policymaking.
An experiment was conducted using DYNAMO simulation to gain an understanding of the relation between the structure and behavior for a well-defined family of nonlinear, second-order systems. The result of the empirical investigation was 1) a taxonomy of structures—a categorization of the structures that give rise to all of the possible behavior modes; and 2) a set of observations and precepts—simply stated guidelines gleaned from the taxonomy that relate structure and behavior.
System Dynamics modeling has been used in the formulation and implementation of strategic planning models for nearly five years within the Long Range and Strategic Studies Division of the British Telecommunications Business. This modelling has proceeded in close collaboration with the Department of Control and Management Systems of Cambridge University. The business itself is a public corporation which means that despite a certain degree of autonomy, it is still ultimately dependent upon the Government for approval of its investment plans and also its investment capital.
Mini-DYNAMO has been adapted for the Apple II computer operating under Apple’s PASCAL system. Working within the constraints of a micro-computer, Micro-DYNAMO offers surprising capacity and speed. Models with up to 25 active equations will run in tolerable lengths of time, and models with up to 100 active equations can be run, although the time required to simulate them is rather long.
Stochastic aspects of systems have generally been ignored in most system dynamics studies except for purposes of sensitivity testing. Yet any model that claims to be more than simply an empirical description of a system must treat the underlying stochasticity explicitly in terms of its contribution to the dynamics. Recent work in chemical, biological, and hydrodynamic systems has shown that the aggregation of stochastic effects can lead to novel behavior (self-organization in dissipative systems). In this paper, an analogy between models of these physical and system dynamics models is developed, in which system dynamics models are seen to be an approximation (to lowest order in an expansion in system size) to a stochastic model for the system. The implications of theoretical results derived for the physical system models are evaluated for their application to the system dynamics models. A research strategy to elaborate this to analyzing systems is proposed.
The oil tanker market is interesting from a system dynamics point of view. The market exhibits regularities which appear to be caused by an underlying structure which has been stable for at least 30 years, and probably longer. This seemingly stable structure is primarily the result of the systematic, but not particularly rational, behaviour of the main actor in the oil tanker market: the community of shipowners. The collective effect of their individualistic actions, I believe, is a rather violent and rhythmic development in the market- on a timescale of years to decades. The regularity is, of course, superimposed on a non-recurring pattern of developments caused by events entirely outside the control of the oil tanker community. In this paper I describe the stable structure and discuss what it means for the likely development of the oil tanker market over the next decade.
Civil Engineer curricula are made up courses. Curricula also lead to degrees and most engineering curricula provide rather narrow time allocation to fundamental categories of course offering. It is usually a tight curricula, designed to be achieved in four calendar years by the good student, five by the average. It is sequestial in nature. The upper limit of course hours is usually a constraint, the addition of new course material must be at the expense of older material. The present curricula are built on science, math, chemistry physics, tools (drafting, surveying, computer programming, statistics), mechanics, dynamics, thermo and materials followed by general engineering and then the various components of civil engineering, such as hydraulics, transportation, sanitary, water resources, structures, materials, etc. This sequence presently produces a B.S. degree holder, ready to emerge on the scene at $18,000 - $30,000/year.
A number of high technology firms have recently reported increasing delays in the development of computer-related hardware and software. Experiencing increasing product development times and schedule overruns, one such company commissioned a system dynamics study of the management of its product development group. The purpose of this study has been to uncover potential sources for rising product development times in the company and to identify those over which management can exercise some control.
System Dynamics models have been used extensively for depicting the dynamic behavior which arises from a given underlying feedback structure. In a typical application, a feedback structure is specified, numerical values for model parameters are specified, and then a base-run simulation is conducted. Following the establishment of a Base Case, initial conditions, table functions, constants, policy variables and exogenous inputs are altered; with the resulting impact on model behavior noted and analyzed.
With the goal of introducing system dynamics to high school students, a set of six learning packages were written during the 1979-80 academic year under grant number GOD7903439 from the US Office of Education. Co-authors of the material are Nancy Roberts, David Anderson, Ralph Deal, Michael Garet, and William Shaffer. The evaluations from pilot testing done during the grant year in six Greater Boston high schools suggest that the materials indeed can effectively accomplish this introductory role. The teachers involved generally made very positive comments about both the value of system dynamics as an exciting high school project as well as the appropriateness of particular materials.
Although the system dynamics literature covers issues of how to construct, analyze, test, validate, and implement dynamic models, surprisingly little attention has been paid to how managers react to and interpret the output from system dynamics models (see Gardiner and Ford, 1980; Rohrbaugh and Anderson, 1979). That is, system dynamicists construct feedback models that are simplifications of a complex reality and then conduct policy tests on these abridged representations. However, decision makers not trained in system dynamics may find that even these allegedly simplified models may be quite complex and difficult to evaluate, since model output typically consists of scores of variables interwoven over time.
This paper attempts to explain the causes of widespread rural poverty which has persisted in Pakistan in spite of the development effort. The paper also analyses the various rural development policies implemented and explains why these policies have had little if any impact on the income of the rural poor. The main instrument of analysis of the study is a system dynamics model incorporating income generation and disbursement processes in an agrarian economy consisting of a capitalist sector and a self-employed sector. The analysis takes into account only the economic factors arising out of the rational decisions of the capitalists and the cultivators. These factors are considered adequate for maintaining rural poverty, although, the role of social and political factors is acknowledged. The study suggests that the absence of an economic force that should encourage ownership of land by its cultivators is a key factor responsible for the poor economic condition of the working rural households. Land is easily separated from cultivators and is concentrated in the capitalist sector. This concentration significantly reduces income in self-employment and thus leaves the cultivators with very little bargaining power for negotiating compensation for labor. Thus, development policies striving to increase productivity may only serve to increase the claim to income on the basis of ownership of resources. If ownership is concentrated outside of the cultivators, such policies may worsen economic condition of the cultivators. The study proposes a general framework for rural development incorporating simultaneously fiscal instruments that should encourage transfer of land ownership to its cultivators and policies that should help increase productivity of land.
Alcohol abuse and treatment in the United States cost nearly $43 billion in 1975- including $19.64 billion in lost production, $12.74 billion in health and medical costs, $5.4 billion in motor vehicle accidents, $2.86 billion in violent crimes, $1.94 billion in social responses, and $0.43 billion in fire losses. There are about 13 million problem drinkers (including alcoholics) in the United States. Of these, less than 10 percent seek treatment. For those receiving treatment, the overall improvement rate ranges from 30 to 70 percent, depending on how broadly improvement is defined.
Dramatic declines in harvests strengthen the assumption that Long Island’s hard clam fishery may be heading for collapse. A family of predator-prey models has been developed to test and evaluate alternative strategies to reverse the decline in hard clam harvests and/or stabilize the clam population. Harvesting is simulated as a fixed percent of standing stock and the behavior of the baymen in response to price and supply of clams is not included in the models. Five types of policies are evaluated: closed season, maximum size limit, hatchery seeding, bounty on predators, and nursery sanctuaries (closed areas). Effectiveness is judged for both the short term (ten years) and the long term (eleven to twenty years after the policy was instituted). While seeding options produce modest short term improvement in the annual value (8.0 to 10.8 percent), only the two bounty policies produce significant improvement in both the short term (17.0 and 72.6 percent) and the long term (20.4 and 66.4 percent). The results of this model reflect the influence of specific management policies on the biological system alone. A later version, incorporating the behavior of the baymen, will introduce key social and economic factors.
This paper explores the following questions: 1.What are the economic consequences of escalations in unconventional energy costs on terms of economic growth, inflation, real energy prices, energy production, consumption, and imports? 2. To what extent are escalations internally generated by interactions between the energy sector and the rest of the economy?
There has been a dramatic upheaval in our conception of science in recent years. The old notion that science is a logical, rational enterprise continually adding to the stockpile of knowledge has been challenged; many now recognize that the evolution of science is punctuated by violent disruptions. During such crises, or scientific revolutions, a tried and true theory is abandoned for an untested and often heretical alternative. The new theory destroys the old rather than building upon it, and thought he successor may flourish for centuries eventually another crisis develops and another revolution occurs. Some even claim that science is completely anarchic, more a no-holds-barred brawl than a calm, reasoned investigation of reality.
As a novice System Dynamicist one learns all the textbook rules and advice of system dynamics modeling. As a practicing System Dynamicist one learns the many shades of rules and advice. The latter ones are only occasionally spoken about and seldom written down. The experience gained from applying formal modeling technique to a diffuse ambiguous reality, often exist as vague mental models of the various roles a formal simulation model and a policy analyst can play in the public policy formation process.
In the first lecture of the first system dynamics course I ever took the professor presented a list of the steps of a modeling project. During the rest of the semester it became apparent to all of us that actual projects never follow the list very closely. But it also became apparent that the list was useful anyway. It helped organize effort, gave direction to a stalled modeler, and provided a checklist of activities to be addressed (if not always accomplished).
A System Dynamics project for a corporate client generally has three objectives: creation of an analytical tool, transfer of a new analysis technology into client organization, and managerial development. In many ways, the first two objectives are means toward the third. Development of new—and shared- perspectives, attitudes, and behaviors among the senior executives can be the most significant benefit from a System Dynamics project. This paper discusses how the process of System Dynamics has been used to draw out diverse points of view, to test and evaluate the differences, to build a consensus regarding key assumptions, to create confidence in the analytical tool which was developed, and, ultimately, to forge a managerial commitment to a new business strategy. The author draws upon several recent applications in the United States and Europe to illustrate the role of System Dynamics in effecting strategy change, and comments on how the process is affected by differences in organizational “culture”.
This paper introduces an aggregate view of factors and policies that can influence the development of military forces in two international alliances which see each other as potential adversaries. The growth of forces observed in the NATO and Warsaw Pact alliances is taken as a reference mode. A conceptual System Dynamics Model is described which can accommodate a number of different perspectives on this issue.
There is a growing interest in energy and energy policy analysis because of the gap between the United States’ energy consumption and energy production. Numerous policies for dealing with America’s “energy crisis” have been discussed and evaluated. Underlying these policy investigations have been a variety of simulation models designed to analyze energy demand, energy supply, and the interaction between the two. Several of the models used for energy policy analysis do not couple the energy sector to the rest of the economy. Some modeling efforts even assume that there is no causality from energy to GNP. The purpose of this study is to examine the structural relationships that govern the interaction between the energy sector and the rest of the energy policies, so as to contribute to the development of more effective national energy policies. A computer simulation model that illuminates the feedback coupling between the energy sector and the rest of the U.S. economy is used in the analysis. The model is used to analyze the effects of increasing capital intensity of the energy sector on the level of economic output and the efficiency of a general class of conservation initiatives in mitigating those effects. When conservation initiatives are introduced, cumulative energy consumption is reduced and sales and profits of the producing sectors are lower. Average GNP is lower and average general unemployment is higher when conservation is introduced.
This paper describes the application of System Dynamics in what is traditionally a hard engineering area, but where the application of analytical techniques are limited by the stochastic nature of the system driving forces (coalface output rates) and the need for highly credible, management orientated results. Methods and analysis have thus centered on using discrete simulation techniques based on open system models, primarily to assist in capacity design. The use of System Dynamics in this context is based on two premises. The first of these is that System Dynamics has, in addition to it s softer areas of application, considerable potential to both supplement and enhance Operational Research approaches in the analysis of such systems. Secondly, it is the author’s belief that the key to further development and acceptance of System Dynamics lies in bridging the gap between itself and associated subject fields, such as Operational Research, by direct demonstration of the approach within these fields. Recent technological advances within the coal clearance field have provided an excellent form for such a demonstration.
Corporate modeling in general and System Dynamics modeling in particular have now a history of more than two decades. Despite this fact impacts on the corporate planning process have not been very satisfactory. The reason is that in many cases system dynamics models (as well as other types of corporate models) had not been constructed, validated and implemented adequately for managerial use. They did not provide the information support which is needed in order to make the necessary decision in the various phases of a complex planning process that has a lot to do with major changes in markets, products, production processes, technologies, governmental regulations etc. Here, formal decisions rules as used in operation planning are impractical in most cases.
The paper reviews, briefly, the development of system dynamics (SD) and presents a modern control approach. It formulates and solves the SD policy design problem as a model-following control system design problem in an adaptive control framework. A computationally simple policy algorithm based on variable-structure system theory is used as an illustrative example of the stabilization of the dynamic characteristics of a production/raw materials system. Computer simulation results are given for the modern control approach as well as the classical SD techniques. Directions in which the modern control approach could be developed are indicated.
This paper describes the development of a limited resource, backward scheduling, network model for an assembly department using DYNAMO. The model evolved in three stages: a calculation device, a policy exploration tool and a planning and scheduling system. An interesting feature of the model is the representation of the complex flow through various disassembly operations. Graphics and report interfaces with DYNAMO are discussed. The enclosed programs are provided on an as-is basis, without warranty either express or implied. No assurance of successful installation can be given.