COCO (Comparing Continuous Optimizers) is an open-source platform for benchmarking singleobjective and multiobjective optimizers on a black-box setting. It facilitates benchmarking of optimization algorithms by automatizing this procedure and providing data of previously run algorithms for comparison.
F.12 Improvements to an existing service
COBISS.SI-ID: 31245095An interview for the Gea magazine, where we discuss the use of evolutionary algorithms for solving multiobjective optimization as well as women in computer science.
F.35 Other
COBISS.SI-ID: 31051047This lecture introduces students to multiobjective optimization with evolutionary algorithms. It presents the basic concepts of multiobjective optimization, the challenges of comparing nondominated solution sets and three different approaches to solving multiobjective problems. It uses examples to show the characteristics of real-world optimization problems and present the mechanisms of evolutionary algorithms, which make it possible to solve such problems efficiently. The lecture concludes with the presentation of additional challenges of multiobjective optimization, such as many objectives, problems with constraints and expensive solution evaluations.
B.04 Guest lecture
COBISS.SI-ID: 30943015