IE 321 • Final • Dynamic and Nonlinear Programming

Multivariable Unconstrained Optimization

Convexity

Gradient Search Algorithm

Example 1

KKT Conditions

Example 1

Reminder: Two-Phase Method

Modified Simplex Method

Example 2

Why do we need them?

Local Search/Iterated Local Search

Simulated Annealing

Genetic Algorithm

Tabu Search

What is a Markov Chain?

One-Step Transition Probabilities

Example

n-Step Transition Probabilities

Chapman-Kolmogorov Equations

Example

Unconditional State Probabilities

Example

Steady State Distribution

Example

Classes and State Properties

Periodicity and Ergodic Markov Chains

Example

Example

Example

First Passage Times

Example

Expected First Passage Time

Expected Recurrence Time

Example

Absorbing Chains

Absorption Probabilities

Example

Probability of Ever Visiting a State

Example

Expected Number of State Visits

Example

Expected Time Until Absoption

Example

Multivariable Unconstrained Optimization 1

Multivariable Unconstrained Optimization 2

Multivariable Unconstrained Optimization 3

Multivariable Unconstrained Optimization 4

Multivariable Unconstrained Optimization 5

Constrained Optimization 1

Constrained Optimization 2

Constrained Optimization 3

Constrained Optimization 4

Metaheuristics 1

Metaheuristics 2

Metaheuristics 3

Markov Chains 1

Markov Chains 2

Markov Chains 3

Markov Chains 4

Markov Chains 5

Markov Chains 6

Markov Chains 7 (Eğer İşlenirse)

Markov Chains 8 (Eğer İşlenirse)

Markov Chains 9 (Eğer İşlenirse)

Markov Chains 10 (Eğer İşlenirse)