SIMULATION: Transactions of The Society for Modeling and Simulation International

doi: 10.1177/003754977502400101pmid: N/A

McLeod, John; McLeod, Suzette

doi: 10.1177/003754977502400109pmid: N/A

Olver, Leon A.; Burwell, Brian H.; Brewer, John W.

doi: 10.1177/003754977502400102pmid: N/A

This paper compares a new rather general modeling procedure with "static" and "dynamic" econometric procedures. The resulting models can all be used to make projections of demand for natural resources.If such models are combined with supply models, one can estimate the Long-term impact of resource policy. The particular resource discussed in this paper is natural gas in the Pacific Gas and Electric (PG&E) service area of California (large portions of the north and central sections of the state).Of the three modeling procedures discussed, the most general is emphasized in this paper. This method, described in Section 3, is related to the modeling procedure proposed by Forrester10,11combined with parameter identification.2,19,30A precise state ment and critique of the method is provided by Mitchiner et al.19The other two modeling proce dures, chosen for purposes of comparison, are stan dard econometric methods. The first of these is a modification of "static" (algebraic) linear regres sion modeling. The second is a "dynamic" linear regression procedure wherein a lagged value of demand is used as one of the input variables.1,3,5The proposed general methodology was not inferior to the two "standard" procedures in any case investigated and was clearly superior in the analysis of firm in dustrial demand for natural gas. This result was expected because the standard procedures are special cases of the proposed methodology.

Arthur Mihram, G.

doi: 10.1177/003754977502400103pmid: N/A

The question of the need for "camps" of simulationists (the "deterministic-continuous" and the "stochastic-discrete" camps) is addressed by delineating both the differences and the likenesses of their approach.

Lucas, John J.; Wait, John V.

doi: 10.1177/003754977502400105pmid: N/A

This paper describes a batch-mode FORTRAN-based continuous-system simulation Language that retains the features of the DARE family of languages1,2,3but is structured to facilitate implementation on a wide variety of computer systems. Except for a small set of necessarily system-dependent routines (for character packing and unpacking, job abortion, etc.) the system is coded entirely in FORTRAN IV. It is highly modular, and uses system-independent FORTRAN-based methods for writing and manipulating solution files on mass storage. The system has thus far been run on a CDC-6400 (requiring about 21,000 decimal words of core memory), and a DEC-10 (requiring about 17,000 words). This paper announces the availability of DARE P, which we plan to make available to interested users who would like to implement it on their particular system, without the usual high surcharge that often accompanies other similar software packages.Our DARE IIIB, 3 which was specifically coded for the CDC-6000 series computers (including a COMPASS assembly-language translator overlay), was not portable. It has, nevertheless, been distributed and successfully used at many installations around the world. DARE P (Differential Analyzer REplacement- Portable) has been developed in response to requests for a version that would run on other computers. It is easy for the user to modify, e.g., he can easily add new integration rules, run-time strategies, or special library subprograms. DARE P can accommo date problems with 100 parameters and 200 state or output variables.In DARE P problem equations are entered in a form close to ordinary mathematical notation; the associ ated procedural language is FORTRAN. User-chosen variable names in the problem description are accommo dated by a special translator overlay which translates DARE problem statements into FORTRAN IV subprograms and builds a communication file. Run-time data is entered via free-form data cards. A variety of out put options are provided, including line-printer listings and plots, and CalComp plotter displays.Complete simulation studies may be directed by a FORTRAN-coded logic block. Single- or multiple-run problems may be specified with storage files used for saving output data for subsequent cross-plotting, reentry into future runs, etc. DARE P includes an internal collection of library functions, and the user may add his own special functions written in FORTRAN and his own one- or two-variable table-lookup function- generators. DARE P provides a choice of several internal fixed- and variable-step integration routines.

Bui, T.D.

doi: 10.1177/003754977502400106pmid: N/A

Wait, John V.

doi: 10.1177/003754977502400107pmid: N/A

Ung, Man T.

doi: 10.1177/003754977502400108pmid: N/A

Young, Jeffrey W.; Mitchiner, John L.; Watt, Kenneth E. F.; Brewer, John W.

doi: 10.1177/003754977502400104pmid: N/A

Simulation models can be used to examine hypothetical long-term causal pathways. This note describes such a model of the interaction of the agricultural and energy sectors at the national level. The indication is that crude-oil prices could have dramatic effects on the long-term and transient values of modal split, wheat exports, urban land conversion rates, and many other systems variables.