1 research outputs found
Robust Multi-Modal Optimisation
Robust and multi-modal optimisation are two important topics that
have received significant attention from the evolutionary computation
community over the past few years. However, the two topics
have usually been investigated independently and there is a lack of
work that explores the important intersection between them. This is
because there are real-world problems where both formulations are
appropriate in combination. For instance, multiple ‘good’ solutions
may be sought which are distinct in design space for an engineering
problem – where error between the computational model queried
during optimisation and the real engineering environment is believed
to exist (a common justification for multi-modal optimisation)
– but also engineering tolerances may mean a realised design might
not exactly match the inputted specification (a robust optimisation
problem). This paper conducts a preliminary examination of such
intersections and identifies issues that need to be addressed for
further advancement in this new area. The paper presents initial
benchmark problems and examines the performance of combined
state-of-the-art methods from both fields on these problems.This work was supported by the Engineering and Physical Sciences
Research Council [grant number EP/N017846/1]