Section: New Results

Performance Assessment in Multiobjective Optimization

In the context of performance assessment in multiojective optimization, two contributions have been made in 2017. First, we proposed a new visualization method to quantitatively assess the performance of multiobjective optimizers (for 2-objective problems) in the form of average runtime attainment functions [6]. The main idea is to display, for each point in objective space, when (in terms of the average runtime) it has been attained or in other words when it has been dominated by the algorithm. Second, we continued our effort towards automated benchmarking via our COCO platform and described a generic test suite generator that can produce test suites like the previous bbob-biobj test suite for an arbitrary number of objectives(Paper to be submitted to the Evolutionary Computation journal and to arXiv/HAL in January 2018.).