STROBOSCOPE Description 

STROBOSCOPE is a general-purpose discrete-event simulation programming language and system for modeling a wide range of complex processes, such as those in construction,  transportation, manufacturing, the health services, etc. It was developed as part of the doctoral research of Julio C. Martinez in the Construction Engineering and Management program at the University of Michigan under the direction of Professor Photios G. Ioannou. Its development was partly supported by the National Science Foundation (Grant CMS-9415105). The name STROBOSCOPE is an acronym for STate- and ResOurce-Based Simulation of COnstruction ProcEsses and reflects the system's major design objective: the ability to make complex dynamic decisions and control the simulation at run-time, based on the current system state and the characteristics, attributes, and state of resources.

STROBOSCOPE's design is based on three-phase activity scanning and not process interaction like most other simulation systems.  The activity-scanning simulation paradigm enables STROBOSCOPE to model the complex resource interactions that characterize cyclic operations without the need to make a distinction between the resources that serve (servers or scarce resources) and those served (customers or moving entities). STROBOSCOPE simulation models use a graphical network-based representation similar to activity cycle diagrams.

A detailed description of STROBOSCOPE can be found in J.C. Martinez's Ph.D. dissertation, which along with several annotated simulation examples are included with STROBOSCOPE. Additional detailed examples can be found in the publications that can be downloaded from this website. The STROBOSCOPE installation package also incudes EZStrobe and ProbSched, which use STROBOSCOPE as the back-end simulation engine.

Both EZStrobe and ProbSched are examples of special-purpose STROBOSCOPE shells that do not require learning the STROBOSCOPE language.

Stroboscope, EZStrobe, ProbSched, Vitascope and Vitascope++ are based upon work supported by the National Science Foundation under Grants No. 9733267, No. 0113890, and No. 0732560. Any opinions, findings, and conclusions or recommendations are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.