Real world examples will be used to illustrate various modeling techniques and solution processes. This course serves as a prerequisite for the Optimization II course in which more advanced topics such as nonlinear programming, integer programming, Markov chains, probabilistic dynamic programming, queuing theory, and queuing theory will be taught. Grading Students will be graded based on their performance on exams and individual exercises. Reference Books Dimitris Bertsimas and John N. Tsitsiklis, Introduction to Linear Optimization , Athena Scientific, 1997. Ronald L. Rardin, Optimization in Operations Research , Prentice Hall, 1998.
Complexity is the prodigy of the world.
Simplicity is the sensation of the universe. Behind complexity, there is always simplicity to be revealed. Inside simplicity, there is always complexity to be discovered. Your Comments and Questions are welcome.