Multi-point acquisition function for constraint parallel efficient multi-objective optimization
Genetic and Evolutionary Computation Conference (GECCO), pp. 511–519
Abstract
Bayesian optimization is often used to optimize expensive black box optimization problems with long simulation times. Typically Bayesian optimization algorithms propose one solution per iteration. The downside of this strategy is the sub-optimal use of available computing power. To efficiently use the available computing power (or a number of licenses etc.) we introduce a multi-point acquisition function for parallel efficient multi-objective optimization algorithms. The multi-point acquisition function is based on the hypervolume contribution of multiple solutions simultaneously, leading to well spread solutions along the Pareto frontier. By combining this acquisition function with a constraint handling technique, multiple feasible solutions can be proposed and evaluated in parallel every iteration. The hypervolume and feasibility of the solutions can easily be estimated by using multiple cheap radial basis functions as surrogates with different configurations. The acquisition function can be used with different population sizes and even for one shot optimization. The strength and generalizability of the new acquisition function is demonstrated by optimizing a set of black box constraint multi-objective problem instances. The experiments show a huge time saving factor by using our novel multi-point acquisition function, while only marginally worsening the hypervolume after the same number of function evaluations.
Authors 3
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Affiliation as printed
Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
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Affiliation as printed
Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
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Affiliation as printed
Leiden Institute of Advanced Computer Science, Leiden, The Netherlands
Cited by 3 stored of 8
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References 29
-
W2805358412details pending0citations
-
W2773031903details pending0citations
-
W2743733467details pending0citations
-
W1595797227details pending0citations
-
W3033040962details pending0citations
-
W2051075114details pending0citations
-
W1553573873details pending0citations
-
W1912576130details pending0citations
-
W2038636756details pending0citations
-
W2317808322details pending0citations
-
W2731819575details pending0citations