SIMULATION: Transactions of The Society for Modeling and Simulation International

Wildberger, A. Martin

doi: 10.1177/003754979406200601pmid: N/A

de Albornoz, Alvaro; Cellier, François E.

doi: 10.1177/003754979406200602pmid: N/A

This paper represents an addendum to an earlier paper published by the same research group in SIMULATION in 1989. In the earlier paper, a crisp inductive reasoner had been employed to qualitatively reason about the behavior of a quantitatively simulated B- 747 aircraft, to determine when a structural malfunction occurs, to hypothesize about the nature of this malfunction, and to decide upon a global strategy that allows operation of the quantitative aircraft model under the modified flying conditions.In the addendum, the formerly crisp inductive reasoner has been replaced by a fuzzy inductive reasoner. The paper demonstrates the enhanced discriminatory power and the improved forecasting capability of the modified reasoning scheme. In addition, the fuzzy inductive reasoner allows prediction of a quasi-continuous response spectum, whereas the crisp inductive reasoner was able to predict discrete (class) values only.

Lilegdon, William R.; Martin, David L.; Pritsker, A. Alan B.

doi: 10.1177/003754979406200603pmid: N/A

This paper presents a formal description of FACTOR/AIM™, a complete manufacturing simulation system. AIM contains a manufacturing modelling language, a simulation analysis program, a problem definition interface and a database for storing inputs, models, animations, simulation outputs and analysis procedures. These components of AIM are integrated in a seamless manner to facilitate both their concurrent and batch execution. AIM also provides utility programs for importing and exporting data to the AIM data base. The focus of the article is to provide a basic understanding of a manufacturing simulation system.

DeArmon, James S.

doi: 10.1177/003754979406200604pmid: N/A

Pseudo-random numbers are widely used in Operations Research and applied mathema tics. With the growth in power of computers and languages, there is some tendency to use lower-significant bits within the pseudo- random number. Theoretical and empirical tests have not been sufficient to assess the randomness of these low-order bits. We show here for two generators that the low- order bits can be empirically tested, after first undertaking a bit-level transformation of the numbers.

O'Neill, Brian

doi: 10.1177/003754979406200605pmid: N/A

Sharma, Ghanshyam; Asthana, R.G.S.; Goel, Suneeti

doi: 10.1177/003754979406200606pmid: N/A

This paper describes a decision support system developed to assist railroad managers in day-to-day as well as long term planning of train operation and study advantages of augmentation of infrastructure. The model simulates train movements on a railroad based on track geometry, speed restrictions, locomotives & wagon characteristics, train schedule and interaction with all other trains over a section and/or a corridor. The model helps in introducing and optimally scheduling train services.An attempt has been made in this paper to exploit potential of AI, Simulation, and operational research (OR) techniques. The user is presented with an integrated environment enabling him to easily modify, validate and implement different methods of train operation through an English-like knowledge-base, and to simulate train operations to carry out studies for different trafic mixes, track geometry, assigning blocks and temporary speed restrictions and failure conditions.

Wilsey, Philip A.

doi: 10.1177/003754979406200607pmid: N/A

Akiyama, Mamoru

doi: 10.1177/003754979406200608pmid: N/A

Smith, Roger

doi: 10.1177/003754979406200609pmid: N/A

McLeod, John; McLeod, Suzette; Roth, Paul F.

doi: 10.1177/003754979406200610pmid: N/A