An Efficient Algorithm for Computing Hypervolume Contributions
The hypervolume indicator serves as a sorting criterion in many recent multi-objective evolutionary algorithms (MOEAs). Typical algorithms remove the solution with the smallest loss with respect to the dominated hypervolume from the population. We present a new algorithm which determines for a popul...
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| Published in | Evolutionary computation Vol. 18; no. 3; pp. 383 - 402 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
One Rogers Street, Cambridge, MA 02142-1209, USA
MIT Press
01.09.2010
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1063-6560 1530-9304 1530-9304 |
| DOI | 10.1162/EVCO_a_00012 |
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| Summary: | The hypervolume indicator serves as a sorting criterion in many recent multi-objective evolutionary algorithms (MOEAs). Typical algorithms remove the solution with the smallest loss with respect to the dominated hypervolume from the population. We present a new algorithm which determines for a population of size
with
objectives, a solution with minimal hypervolume contribution in time
(
log
) for
> 2. This improves all previously published algorithms by a factor of
for all
> 3 and by a factor of
for
= 3.
We also analyze hypervolume indicator based optimization algorithms which remove λ > 1 solutions from a population of size
= μ + λ. We show that there are populations such that the hypervolume contribution of iteratively chosen λ solutions is much larger than the hypervolume contribution of an optimal set of λ solutions. Selecting the optimal set of λ solutions implies calculating
conventional hypervolume contributions, which is considered to be computationally too expensive. We present the first hypervolume algorithm which directly calculates the contribution of every set of λ solutions. This gives an additive term of
in the runtime of the calculation instead of a multiplicative factor of
. More precisely, for a population of size
with
objectives, our algorithm can calculate a set of λ solutions with minimal hypervolume contribution in time
(
log
+
) for
> 2. This improves all previously published algorithms by a factor of
for
> 3 and by a factor of
for
= 3. |
|---|---|
| Bibliography: | Fall, 2010 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
| ISSN: | 1063-6560 1530-9304 1530-9304 |
| DOI: | 10.1162/EVCO_a_00012 |