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1998
Springer

A Spatial Predator-Prey Approach to Multi-objective Optimization: A Preliminary Study

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A Spatial Predator-Prey Approach to Multi-objective Optimization: A Preliminary Study
This paper presents a novel evolutionary approach of approximating the shape of the Pareto-optimal set of multi-objective optimization problems. The evolutionary algorithm (EA) uses the predator-prey model from ecology. The prey are the usual individuals of an EA that represent possible solutions to the optimization task. They are placed at vertices of a graph, remain stationary, reproduce, and are chased by predators that traverse the graph. The predators chase the prey only within its current neighborhood and according to one of the optimization criteria. Because there are several predators with different selection criteria, those prey individuals, which perform best with respect to all objectives, are able to produce more descendants than inferior ones. As soon as a vertex for the prey becomes free, it is refilled by descendants from alive parents in the usual way of EA, i.e., by inheriting slightly altered attributes. After a while, the prey concentrate at Pareto-optimal positions....
Marco Laumanns, Günter Rudolph, Hans-Paul Sch
Added 06 Aug 2010
Updated 06 Aug 2010
Type Conference
Year 1998
Where PPSN
Authors Marco Laumanns, Günter Rudolph, Hans-Paul Schwefel
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