SIMULATION: Transactions of The Society for Modeling and Simulation International

McLeod, John; McLeod, Suzette

doi: 10.1177/003754977402300106pmid: N/A

Pritsker, A. Alan B.

doi: 10.1177/003754977402300101pmid: N/A

Levine, Leon

doi: 10.1177/003754977402300102pmid: N/A

Light, Richard A.; Johnson, R. Curtis

doi: 10.1177/003754977402300103pmid: N/A

The planning of a community's development and opera tions, whether for a small town or an international project, requires the allocation of resources to various areas of endeavor. These resources can best be allocated if a reasonably accurate estimate is made of the needs for corrective action and the effectiveness of it as a function of the type and amount of expenditure. For example, an estimate may be made of the amount of pollution and social conflict which may develop and of the effectiveness of various physical and human countermeasures (sewage disposal facilities, air pollution control, police, hospitals, etc.); on this basis a reasonable allocation may be made. Such a procedure forces one to establish value systems in order to assess social costs on a basis compatible with real costs. This is difficult. Few planners understand the philosophical and long- term implications of their actions.The approach adopted in this paper bears great similarity to optimal process control by computer, but it cannot solve problems unless suitable value systems can be established. Even when values cannot be adequately established, however, this approach to examining community problems allows decision- makers to better understand the implications of their actions. This approach helps educators to better plan programs which differ from the tradi tionally narrow engineering curricula and to intro duce the concept that technical tools and techniques have important applications in politics and philosophy.

Novak, Lawrence T.; Coulman, George A.

doi: 10.1177/003754977402300104pmid: N/A

Brandon, Daniel M.

doi: 10.1177/003754977402300105pmid: N/A

This report describes and illustrates a new nonlinear single-step implicit method for the numerical integra tion of general differential systems. The method is A-stable, operates with fixed or variable step size, is computationally fast, and has accuracy comparable to or better than that of other widely used methods. This paper reports computational experiments using this new method and compares the results with those obtained using other integration algorithms, includ ing high-order methods. The comparisons are generally favorable to the new method. The method is applicable to both "stiff" and "nonstiff" systems. On stiff systems the new method was much more accurate than any of the other algorithms tested.