ISYE 6644 - MODULE 1 QUESTIONS
AND ANSWERS 2026
Simulation Model - ANSWERSA high-level representation used to imitate the operation
of a real-world process or system over time.
Discrete Model - ANSWERSA model where the state of the system changes only at a
countable number of points in time.
Stochastic Model - ANSWERSA model that incorporates randomness or probability into
its operation.
Dynamic Model - ANSWERSA model that evolves or changes over time.
Analytic Methods - ANSWERSMathematical techniques used to derive exact solutions
or properties of a model.
Numerical Methods - ANSWERSComputational techniques used to approximate
solutions to mathematical models, often when analytical solutions are not feasible.
Simulation Methods - ANSWERSTechniques that involve imitating the operation of a
system over time to study its behavior and draw inferences.
Verification - ANSWERSThe process of ensuring that the simulation model is
implemented correctly and that the program runs as intended.
Validation - ANSWERSThe process of determining whether the simulation model is an
accurate representation of the real-world system being studied.
Pseudo-Random Numbers (PRN's) - ANSWERSNumbers generated by a deterministic
algorithm that appear to be random and uniformly distributed between 0 and 1.
Linear Congruential Generator (LCG) - ANSWERSA common algorithm for generating
pseudo-random numbers using a linear recurrence relation modulo m.
Simulation Languages - ANSWERSSpecialized software packages designed to facilitate
the building and running of simulation models (e.g., Arena).
Input Analysis - ANSWERSThe process of identifying, collecting, and statistically
modeling the data that drives a simulation.
AND ANSWERS 2026
Simulation Model - ANSWERSA high-level representation used to imitate the operation
of a real-world process or system over time.
Discrete Model - ANSWERSA model where the state of the system changes only at a
countable number of points in time.
Stochastic Model - ANSWERSA model that incorporates randomness or probability into
its operation.
Dynamic Model - ANSWERSA model that evolves or changes over time.
Analytic Methods - ANSWERSMathematical techniques used to derive exact solutions
or properties of a model.
Numerical Methods - ANSWERSComputational techniques used to approximate
solutions to mathematical models, often when analytical solutions are not feasible.
Simulation Methods - ANSWERSTechniques that involve imitating the operation of a
system over time to study its behavior and draw inferences.
Verification - ANSWERSThe process of ensuring that the simulation model is
implemented correctly and that the program runs as intended.
Validation - ANSWERSThe process of determining whether the simulation model is an
accurate representation of the real-world system being studied.
Pseudo-Random Numbers (PRN's) - ANSWERSNumbers generated by a deterministic
algorithm that appear to be random and uniformly distributed between 0 and 1.
Linear Congruential Generator (LCG) - ANSWERSA common algorithm for generating
pseudo-random numbers using a linear recurrence relation modulo m.
Simulation Languages - ANSWERSSpecialized software packages designed to facilitate
the building and running of simulation models (e.g., Arena).
Input Analysis - ANSWERSThe process of identifying, collecting, and statistically
modeling the data that drives a simulation.
