Nature Inspired Algorithms

information and communication technology

intermediate

LECTURES:

I2_W01, I2_W02, I2_W03

LABORATORIES:

I2_U02, I2_U03, I2_U06, I2_K02

requested basic knowledge concerning probabilistic theory, and computer programming skills.

The course aims to provide knowledge about the structure and operation of various heuristic optimization methods, including those inspired by natural mechanisms, and practical skills in using these methods. The methods find suboptimal solutions to computationally complex problems, the so-called NP-hard problems. The methods are based on a single solution (local search, simulated annealing, tabu) and a population-based approach (evolutionary algorithms, swarm optimization: particle swarms, and ant algorithms). Theory and pseudocodes for each method are provided and discussed. Multi-criteria optimization methods are also briefly discussed. Students are expected to be familiar with at least one computer programming language. As part of laboratory classes, students develop computer programs illustrating subsequent issues presented during the lecture and test them and their effectiveness on classic benchmark sets.

LECTURES

Student

W1 - knows techniques of optimization based on mechanisms of Nature and their applications in selected areas (I2_W01, I2_W02, I2_W03)

LABS

Student

U1 - applies advanced tools and computer science methods based on techniques inspired by Nature in a selected area (I2_U02, I2_U03, I2_U06)

K1 - is ready for systematic work in a project (I2_K02)

For all learning outcomes, the following assessment criteria are adopted for all forms of verification:

grade 5: fully achieved (no obvious shortcomings),

grade 4.5: achieved almost fully and criteria for awarding a higher grade are not met,

grade 4: largely achieved and the criteria for a higher grade are not met,

grade 3.5: largely achieved - with a clear majority of positives - and the criteria for granting a higher grade are not met,

grade 3: achieved for most of the cases covered by the verification and criteria for a higher grade are not met,

grade 2: not achieved for most of the cases covered by the verification.