In almost no other field of computer science, the idea of using bio-inspired search paradigms
has been so useful as in solving multiobjective optimization problems. The idea of using a …

Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

Hypervolume is widely used as a performance indicator in the field of evolutionary
multiobjective optimization (EMO). It is used not only for performance evaluation of EMO …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

For over 25 years, most multi-objective evolutionary algorithms (MOEAs) have adopted
selection criteria based on Pareto dominance. However, the performance of Pareto-based …

The hypervolume measure (or S metric) is a frequently applied quality measure for
comparing the results of evolutionary multiobjective optimisation algorithms (EMOA). The …

Whereas evolutionary multiobjective optimization (EMO) algorithms have successfully been
used in a wide range of real-world application tasks, difficulties in their scalability to many …

We present an algorithm for calculating hypervolume exactly, the Hypervolume by Slicing
Objectives (HSO) algorithm, that is faster than any that has previously been published. HSO …

The hypervolume indicator has frequently been used for comparing evolutionary multi-
objective optimization (EMO) algorithms. A reference point is needed for hypervolume …

We describe a new algorithm WFG for calculating hypervolume exactly. WFG is based on
the recently-described observation that the exclusive hypervolume of a point p relative to a …