  We propose a multi-objective optimization algorithm aimed at achieving good
anytime performance over a wide range of problems. Performance is assessed in
terms of the hypervolume metric. The algorithm called HMO-CMA-ES represents a
hybrid of several old and new variants of CMA-ES, complemented by BOBYQA as a
warm start. We benchmark HMO-CMA-ES on the recently introduced bi-objective
problem suite of the COCO framework (COmparing Continuous Optimizers),
consisting of 55 scalable continuous optimization problems, which is used by
the Black-Box Optimization Benchmarking (BBOB) Workshop 2016.
