# xyz

## xyz軟體王  This is the second course that introduces deterministic and probabilistic optimization models such as dynamic programming, integer programming, nonlinear programming, Markov chain and queueing theory. This course focuses on modeling approaches, fundamental solution methodologies and their applications to the real world.

This is the second course that introduces deterministic and probabilistic optimization models such as dynamic programming, integer programming, nonlinear programming, Markov chain and queueing theory. This course focuses on modeling approaches, fundamental solution methodologies and their applications to the real world.

10.1 A Prototype Example for Dynamic Programming
10.2 Characteristics of Dynamic Programming Problems
10.3 Deterministic Dynamic Programming ─ Example 4改為簡單案例
10.4 Probabilistic Dynamic Programming ─ 僅教Example 6

11.1 Prototype Example
11.2 Some BIP Applications
11.3 Innovative Uses of Binary Variables in Model Formulation
11.4 Some Formulation Examples
11.5 Some Perspectives on Solving Integer Programming Problem
11.6 The Branch-and-Bound Technique and its Application to Binary integer Programming
11.7 A Branch-and-Bounds Algorithm for the Mixed Integer Programming

Review Calculus
12.1 Sample applications
12.2 Graphical Illustration of Nonlinear Programming Problems
12.3 Types of Nonlinear Programming Problems
12.4 One-Variable Unconstrained Optimization
Appendix 3: Constrained Optimization with Equality Constraints
12.5 Multivariable Unconstrained Optimization
12.6 The Karush-Kuhn-Tucker(KKT) Conditions for Constrained Optimization

Review Probability Theory
16.1 Stochastic Processes
16.2 Markov Chains
16.3 Chapman-Kolmogorov Equations
16.4 Classification of States of a Markov Chain
16.5 Long-Run Properties of A Markov Chain
16.6 First Passage Times
16.7 Absorbing States

17.1 Prototype Example
17.2 Basic Structure of Queuing Models
17.3 Examples of Real Queuing Systems
17.4 The Role of the Exponential Distribution
17.5 The Birth-and-Death Process
17.6 Queuing Models Based on the Birth-and-Death Process
17.7 Queuing Models involving Nonexponential Distributions
17.8 Priority-Discipline Queuing Models
17.9 Queuing Networks
17.10 The Application of Queuing Theory

20.1 Simulations
20.2 Simulations
20.3 Simulations
20.4 Simulations

FS Hillier and GJ Lieberman, Introduction to Operations Research, 8th edition, 2005, McGraw-Hill Inc.    