Detail of the student project

List
Topic:Portfolio optimization method with success prediction
Department:Katedra kybernetiky
Supervisor:Ing. Petr Pošík Ph.D.
Announce as:DP
Description:Design a composite optimization algorithm (portfolio algorithm) which automatically chooses the most promising optimization algorithm in the portfolio to run in the next step. Perform a comparison against its constituent algorithms and against other chosen competitors. The comparison shall reveal the differences during the whole course of optimization, not only after the optimization is finished. The COCO framework is a suitable candidate.
Instruction:1. Make a literature survey for similar approaches.
2. Design the algorithm to choose the most promising algorithm in the portfolio.
3. Perform a comparison of the portfolio approach against its constituent algorithms.
4. Perform a comparison of the portfolio approach against other state-of-the-art competitors.
Bibliography:Will be provided by the thesis supervisor.
Realization form:Code in Python, MATLAB, or Java.
Date:10.05.2019
Responsible person: Petr Pošík