The goal is to introduce students with basic principles of optimization and optimal design. In particular, the students are introduced to classical and modern optimization techniques, as well with possible applications in modern architectural and urban design. In addition, the students are familiarized with basic principles of analysis and design of adaptive, optimizing, self-tuning and evolutionary structures and systems.

The students are familiarized with recognizing, properly formulating and efficiently solving optimization and control problems. The students are familiarized with basic principles of optimal design, as well with available algorithms and software solutions. The students are also introduced with properties of modern optimal and evolutionary dynamical systems, and possibilities of utilization of these systems in solving a variety of practical problems.

1. Basic principles of optimization. Formal statement of optimization problem. Classification of optimization problems and algorithms. 2. Classical optimization techniques. 2.1. Unconstrained optimization. Optimization in one and many dimensions, analytic and numeric approach, search methods 2.2. Linear programming 2.3 Basic principles of non-linear programming. Classic numerical methods of non-convex optimization. 3. Modern global optimization techniques 3.1. Evolutionary and genetic algorithms 3.2 Particle swarm optimization 3.3 Ant colony optimization

Lectures. Study. Research