Course Goals: This course will develop a thorough understanding of linear programming and certain stochastic processes, the ability to solve linear programs and stochastic processes' problems, and the ability model standard business problems and other problems using linear programs and stochastic processes.
Course Objectives:
- Develop linear programs from standard business problems
- Develop linear programs from other appropriate applications
- Illustrate how the simplex algorithm solves linear programs
- Develop the code for the simplex algorithm
- Illustrate how integer program algorithms solve integer programs
- Illustrate how duality theory solves linear programs
- Construct a project network and apply program evaluation review technique and critical path management
- Develop code to simulate observations from certain probability distributions
- Develop code to simulate the movement of a Markov chain
- Describe standard properties of Markov Chain and classify a Markov Chain according to them
- Derive the steady state solution and mean first passage matrix of a Markov chain
- Interpret a steady state solution and mean first passage matrix of a Markov chain
- Illustrate how Markov chains can solve standard business problems
- Illustrate how queuing theory can solve problems with inter-arrival and service times exponentially distributed using
Course Outcomes: Student will be able to
- convert standard business problems into linear programs
- convert problems from other appropriate applications into linear programs
- solve linear programs using the simplex algorithm
- code the simplex algorithm
- solve integer programs using integer program algorithms
- solve linear programs using duality theory
- construct a project network and apply program evaluation review technique and critical path management
- code the simulation of observations from certain probability distributions
- code the simulation of the movement of a Markov chain
- classify a Markov Chain according to standard properties
- calculate a steady state solution and mean first passage matrix of a Markov chain
- interpret a steady state solution and mean first passage matrix of a Markov chain
- solve standard business problems using Markov chains
- solve problems with inter-arrival and service times exponentially distributed using queuing theory