activity
20052023
most citedIntroducing machine learning for power system operation support

36 citations · 236 across the 52 of their papers we have counts for

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10 papers · 1 filter

cs.NE2021★ 29 cited

Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics ---22 Years of Paradiseo---

Johann Dreo, Arnaud Liefooghe, Sébastien Verel +5

The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors…

cs.NE2019

On the Behaviour of Differential Evolution for Problems with Dynamic Linear Constraints

Maryam Hasani-Shoreh, María-Yaneli Ameca-Alducin, Wilson Blaikie +2

Evolutionary algorithms have been widely applied for solving dynamic constrained optimization problems (DCOPs) as a common area of research in evolutionary optimization. Current be…

cs.NE2018★ 36 cited

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Joel Lehman, Jeff Clune, Dusan Misevic +50

Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic pr…

cs.NE2014

Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES

Ilya Loshchilov, Marc Schoenauer, Michèle Sebag +1

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimiza…

cs.NE2013★ 9 cited

Sustainable Cooperative Coevolution with a Multi-Armed Bandit

François-Michel De Rainville, Michèle Sebag, Christian Gagné +2

This paper proposes a self-adaptation mechanism to manage the resources allocated to the different species comprising a cooperative coevolutionary algorithm. The proposed approach…

cs.NE2012

Black-box optimization benchmarking of IPOP-saACM-ES and BIPOP-saACM-ES on the BBOB-2012 noiseless testbed

Ilya Loshchilov, Marc Schoenauer, Michèle Sebag

In this paper, we study the performance of IPOP-saACM-ES and BIPOP-saACM-ES, recently proposed self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution Strategies. B…