Multi-level ranking for constrained multi-objective evolutionary optimisation

P Hingston, L Barone, S Huband, L While�- International Conference on�…, 2006 - Springer
International Conference on Parallel Problem Solving from Nature, 2006Springer
In real-world optimisation problems, feasibility of solutions is invariably an essential
requirement. A natural way to deal with feasibility is to cast it as an additional objective in a
multi-objective optimisation setting. In this paper, we consider two possible ways to do this,
using a multi-level scheme for ranking solutions. One strategy considers feasibility first,
before considering objective values, while the other reverses this ordering. The first strategy
has been explored before, while the second has not. Experiments show that the second�…
Abstract
In real-world optimisation problems, feasibility of solutions is invariably an essential requirement. A natural way to deal with feasibility is to cast it as an additional objective in a multi-objective optimisation setting. In this paper, we consider two possible ways to do this, using a multi-level scheme for ranking solutions. One strategy considers feasibility first, before considering objective values, while the other reverses this ordering. The first strategy has been explored before, while the second has not. Experiments show that the second strategy can be much more successful on some difficult problems.
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