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Ilya Loshchilov

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Related publications (18)

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Black-box optimization benchmarking of IPOP-saACM-ES on the BBOB-2012 noisy testbed

Ilya Loshchilov

In this paper, we study the performance of IPOP-saACM-ES, recently proposed self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution Strategy. The algorithm was tested using restarts till a total number of function evaluations of 10^6D was r ...

2012

Alternative Restart Strategies for CMA-ES

Ilya Loshchilov

This paper focuses on the restart strategy of CMA-ES on multi-modal functions. A first alternative strategy proceeds by decreasing the initial step-size of the mutation while doubling the population size at each restart. A second strategy adaptively alloca ...

2012

Adaptive Coordinate Descent

Ilya Loshchilov

Independence from the coordinate system is one source of efficiency and robustness for the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). The recently proposed Adaptive Encoding (AE) procedure generalizes CMA-ES adaptive mechanism, and can be us ...

2011

Not all parents are equal for MO-CMA-ES

Ilya Loshchilov

The Steady State variants of the Multi-Objective Covariance Matrix Adaptation Evolution Strategy (SS-MO-CMA-ES) generate one offspring from a uniformly selected parent. Some other parental selection operators for SS-MO-CMA-ES are investigated in this paper ...

2011

A Mono Surrogate for Multiobjective Optimization

Ilya Loshchilov

Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective Optimization Algorithm (EMOA) in lieu of the actual objectives, without modify ...

2010

This paper discusses the idea of using a single Pareto-compliant surrogate model for multiobjective optimization. While most surrogate approaches to multi-objective optimization build a surrogate model for each objective, the recently proposed mono surroga ...

2010

Taking inspiration from approximate ranking, this paper nvestigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invariance of the approach with respect to monotonous transformations of the fitness function. ...

2010

Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Pareto front with a single model. Such an approach has been recently introduced using a mix ...

2010