GLOBAL OPTIMIZATION

• Brief notes on Local optimization.
• Stochastic approaches to Global Optimization
  1. Multistart based methods
     1. Stopping rules
     2. Single Linkage Clustering
     3. Topographical multilevel Clustering
     4. Typical distance Clustering
  2. Controlled Random Search
  3. Simulated Annealing
• Evolutionary approaches to Global Optimization
  1. Particle Swarm
  2. Genetic algorithms
• Deterministic Methods
  1. Interval Optimization
  2. Tunneling & Filled function Methods
  3. Trajectory methods