The use of simulation for decision making

Schultz, Randall L.

doi:10.1002/bs.3830190507

Cited by 10 publications

(2 citation statements)

References 12 publications

(8 reference statements)

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“…1 . 5 Previous Research on Simulating Human Spatial Behavior and Reponses to Fire : Literature Review During the last fifteen years, there has been considerable interest in the application of computer simulation techniques to the study of human cognitive behavior (Feldman, 1962; Luce and Raiffa, 1964 ; Simon, 1967Simon, , 1969Apter, 1970;Shultz, 1974).…”

Section: Occupanciesmentioning

confidence: 99%

A computer simulation of human behavior in building fires :

Stahl¹

1978

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The author also thanks Drs. Gary Winkel and Susan Saegert of the City University of New York, and Dr. Dane Harwood of the National Bureau of Standards, for their assistance in matters concerning psychological and behavioral theory. The extremely capable technical assistance of Mr. Lawrence Kaetzl in matters involving the use of the Center for Building Technology's INTERDATA 7/32 minicomputer is greatfully acknowledged. Finally, Drs. Edward Arens and Robert Glass, and Mr. James Harris, all of the Center for Building Technology, are acknowledged for their critical reviews of drafts of this report.

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Section: Occupanciesmentioning

confidence: 99%

A computer simulation of human behavior in building fires :

Stahl¹

1978

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“…A basic idea with origins in control engineering is that by modelling a system and its disturbances a control scheme can be designed to regulate the system. This concept has led, in part, to the development of large-scale business simulations for testing alternative decision strategies (Schultz 1974). In this presentation we examine these principles on a more abstract level.…”

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confidence: 99%

Production planning and control II. The planning horizon problem

Willke

Miller

1978

International Journal of Systems Science

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A general model of the production planning and control problem based on modern control theory is given. This model is used to develop principles for planning under uncertainty and to illustrate the strong connection between the structure of the production-inventory system, the characteristics of the environment, and the planning horizon. It is shown that the planning horizon is a function of the structure of both the production-inventory system and the market dynamics. Further, it is shown that the planning horizon is independent of the level of uncertainty and that the planning horizon problem is effectively decoupled from the problems of measuring the state of the production-inventory system and market forecasting. IntroductionThe most vexing problem of production management is uncertaintyuncertainty about market demand, uncertainty about the current status of the production and inventory systems, and uncertainty about the costeffectiveness of production-inventory control policy in meeting demand. Managers attempt to reduce uncertainty by forecasting both market demand and inventory levels. Implicit in these forecasts is a planning horizon-a point in time to which sales forecasts must be made and production planning accomplished. Intuitively, we know that uncertainty grows in some proportion to the length of the planning period. How much, is generally unknown, and even less is known about the impact of uncertainty on system performance. The usual procedure for handling such problems is to decompose the overall production planning and control problem into three general areas: (1) market forecasting; (2) inventory control; and (3) production scheduling. Yet very little is known about the specific information requirements for decision making in large-scale systems; even less is known about the information needs of the individual decision-maker. The tendency of large organizations in the past several years has been to develop and implement vast, expensive, and complex management information systems in the hope that, in supplying large quantities of information, enough would be supplied. This kind of blanket approach too often ignores the basic issues, including the type and quantity of information needed about the organization and its environment, the uses to which information is put, and, more importantly, the relationships between information, decision-making behaviour, and system performance.

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Simulation as Research Method: Modeling Social Interactions in Management Science

Happach

Tilebein

2015

Collective Agency and Cooperation in Natural and Artificial Systems

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The use of simulation for decision making

Cited by 10 publications

References 12 publications

A computer simulation of human behavior in building fires :

A computer simulation of human behavior in building fires :

Production planning and control II. The planning horizon problem

Simulation as Research Method: Modeling Social Interactions in Management Science

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