Ayame/Inria Associate Team "s3-bbo" - Threefold Scalability in Any-objective Black-Box Optimization

This is the web page of the Ayame/Inria associate team “s3-bbo - Threefold Scalability in Any-objective Black-Box Optimization”. It brings together researchers from the TAO and Dolphin Inria teams with researchers from Shinshu University in Nagano, Japan. Additional researchers from the University of Calais are associated to the team as well.

Our common interest is on black-box single and multi-objective optimization with complementary expertise ranging from theoretical and fundamental aspects over algorithm design to solving industrial applications. The work that we want to pursue in the context of the associate team is focused on black-box optimization of problems with a large number of decision variables and one or several functions to evaluate solutions, employing distributed and parallel computing resources. The objective is to theoretically derive, analyze, design, and develop scalable black-box stochastic algorithms including evolutionary algorithms for large-scale optimization considering three different axes of scalability: (i) decision space, (ii) objective space, and (iii) availability of distributed and parallel computing resources. We foresee that the associate team will make easier the existing collaboration, already funded by a joint JSPS project, and open-up a long term fruitful collaboration between Inria and Shinshu University. The collaboration will be through exchanging researchers and Ph.D. students and co-organization of workshops.

Team Members

Shinshu University, Nagano, Japan

Tao project-team, Inria Saclay - Ile-de-France, LRI, Université Paris-Sud, France

Dolphin project-team, Inria Lille - Nord Europe, Univ. Lille, CRIStAL, France

External collaborators

  • Sébastien Verel, Université du Littoral Côte d'Opale, Associate Professor (MCF)
  • Christopher Jankee, Université du Littoral Côte d'Opale, PhD student
  • Alexandre Chotard, Université Paris Sud, PhD student

Associated Scientific Exchanges

2017

2016

2015

Associated Publications

2017

  • Miyako Sagawa, Hernán Aguirre, Fabio Daolio, Arnaud Liefooghe, Bilel Derbel, Sébastien Verel, Kiyoshi Tanaka. Learning variable importance to guide recombination on many-objective optimization. 5th International Conference on Smart Computing and Artificial Intelligence (SCAI 2017), Hamamatsu, Japan, 2017
  • Hugo Monzon, Hernán Aguirre, Sébastien Verel, Arnaud Liefooghe, Bilel Derbel, Kiyoshi Tanaka. Closed state model for understanding the dynamics of MOEAs. Genetic and Evolutionary Computation Conference (GECCO 2017), pp 609–616, Berlin, Germany, 2017
  • Arnaud Liefooghe, Bilel Derbel, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka.Towards landscape-aware automatic algorithm configuration: preliminary experiments on neutral and rugged landscapes. European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2017), Lecture Notes in Computer Science (LNCS), Amsterdam, The Netherlands, 2017
  • Arnaud Liefooghe, Bilel Derbel, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka. A fitness landscape analysis of Pareto local search on bi-objective permutation flowshop scheduling problems. 9th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2017), Lecture Notes in Computer Science (LNCS), vol. 10173, pp. 422-437, Münster, Germany, 2017
  • Youhei Akimoto, Anne Auger and Nikolaus Hansen. Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions, FOGA 2017.
  • Fabio Daolio, Arnaud Liefooghe, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka. Problem features vs. algorithm performance on rugged multi-objective combinatorial fitness landscapes. Evolutionary Computation (to appear)

2016

  • Youhei Akimoto and Nikolaus Hansen. Online Model Selection for Restricted Covariance Matrix Adaptation. PPSN 2016.
  • Youhei Akimoto and Nikolaus Hansen. Projection-Based Restricted Covariance Matrix Adaptation for High Dimension. GECCO 2016.
  • Ait Elhara, O., A. Auger and N. Hansen (2016). Permuted Orthogonal Block-Diagonal Transformation Matrices for Large Scale Optimization Benchmarking. In Genetic and Evolutionary Computation Conference (GECCO 2016), Proceedings, ACM.
  • Miyako Sagawa, Hernán Aguirre, Fabio Daolio, Arnaud Liefooghe, Bilel Derbel, Sébastien Verel, Kiyoshi Tanaka. Learning variable importance to guide recombination. IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (IEEE MCDM 2016), Athens, Greece, 2016
  • Christopher Jankee, Sébastien Verel, Bilel Derbel, Cyril Fonlupt. A Fitness Cloud Model for Adaptive Metaheuristic Selection Methods. International Conference on Parallel Problem Solving from Nature (PPSN 2016), Lecture Notes in Computer Science (LNCS), vol. 9921, Edinburgh, Scotland, 2016
  • Bilel Derbel, Arnaud Liefooghe, Qingfu Zhang, Hernán Aguirre, Kiyoshi Tanaka. Multi-objective local search based on decomposition. International Conference on Parallel Problem Solving from Nature (PPSN 2016), Lecture Notes in Computer Science (LNCS), vol. 9921, pp. 431-441, Edinburgh, Scotland, 2016
  • Arnaud Liefooghe, Bilel Derbel. A correlation analysis of set quality indicator values in multiobjective optimization. Genetic and Evolutionary Computation Conference (GECCO 2016), pp. 581-588, Denver, USA, 2016

2015

  • Saúl Zapotecas-Martínez, Bilel Derbel, Arnaud Liefooghe, Hernán Aguirre, Kiyoshi Tanaka. Geometric differential evolution in MOEA/D: a preliminary study. 14th Mexican International Conference on Artificial Intelligence (MICAI 2015), Lecture Notes in Computer Science (LNCS), vol. 9413, pp. 364-376, Cuernavaca, Mexico, 2015
  • Hernán Aguirre, Saúl Zapotecas-Martínez, Arnaud Liefooghe, Sébastien Verel, Kiyoshi Tanaka. Approaches for many-objective optimization: analysis and comparison on MNK-landscapes. 13th International Conference on Artificial Evolution (EA 2015), Lecture Notes in Computer Science (LNCS) vol. 9554, pp.14-28, Lyon, France, 2015
  • Asma Atamna. Benchmarking IPOP-CMA-ES-TPA and IPOP-CMA-ES-MSR on the BBOB Noiseless Testbed. Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO 2015), pp. 1135-1142, Madrid, Spain, 2015
  • Shinichi Shirakawa and Youhei Akimoto and Kazuki Ouchi and Kouzou Ohara. Sample Reuse in the Covariance Matrix Adaptation Evolution Strategy Based on Importance Sampling. Genetic and Evolutionary Computation Conference (GECCO 2015), pp. 305-312, Madrid, Spain, 2015
  • Saul Zapotecas-Martínez, Bilel Derbel, Arnaud Liefooghe, Dimo Brockhoff, Hernán Aguirre, Kiyoshi Tanaka. Injecting CMA-ES into MOEA/D. Genetic and Evolutionary Computation Conference (GECCO 2015), pp. 783-790, Madrid, Spain, 2015
  • Fabio Daolio, Arnaud Liefooghe, Sébastien Verel, Hernán Aguirre, Kiyoshi Tanaka. Global vs local search on multi-objective NK-landscapes: contrasting the impact of problem features. Genetic and Evolutionary Computation Conference (GECCO 2015), pp. 369-376, Madrid, Spain, 2015 best paper award (ECOM track) ★
  • Dimo Brockhoff. Comparison of the MATSuMoTo Library for Expensive Optimization on the Noiseless Black-Box Optimization Benchmarking Testbed. Congress on Evolutionary Computation (CEC 2015). IEEE, 2015.
  • Bilel Derbel, Arnaud Liefooghe, Gauvain Marquet, El-Ghazali Talbi. A fine-grained message passing MOEA/D. IEEE Congress on Evolutionary Computation (CEC 2015), Sendai, Japan, 2015
 
associateteam.txt · Last modified: 2017/10/11 09:48 by liefooga
Recent changes RSS feed Donate Powered by PHP Valid XHTML 1.0 Valid CSS Driven by DokuWiki