Computational intelligence

 

Computational intelligence is a study of stochastic search, optimization and learning methods, inspired by natural systems. Research in this area at the JSI Department of Intelligent Systems focuses on evolutionary computation and optimization. We study evolutionary algorithms for multiobjective optimization, their enhancement through parallel computing and surrogate models, constraint handling in multiobjective optimization, visualization of optimization results, and optimization algorithm benchmarking.

Our research findings and developed algorithms represent a basis for applications in diverse areas including:

  • Engineering design
  • Manufacturing
  • Scheduling
  • Energy efficiency
  • Product quality control
  • Transportation
  • Space exploration
  • Epidemiology

Contact Bogdan Filipič

CURRENT PROJECTS

Artificial intelligence and intelligent systems

Artificial intelligence and intelligent systems

V. Janko, M. Gams, B. Filipič, T. Šef, M. Luštrek, T. Tušar, A. Gradišek, E. Dovgan, M. Mlakar, J. Krivec,...

Characterization of constrained continuous multiobjective optimization problems

Characterization of constrained continuous multiobjective optimization problems

A. Vodopija (Supervised by B. Filipič) Within the doctoral research project, we aim at characterizing constrained continuous multiobjective optimization problems...

Simulation-based optimization of cogging torque in electric motor design

Simulation-based optimization of cogging torque in electric motor design

B. Filipič, T. Tušar, A. Vodopija This applied project deals with simulation-based optimization in electric motor design. The task is...

Constrained multiobjective optimization based on problem landscape analysis

Constrained multiobjective optimization based on problem landscape analysis

B. Filipič, T. Tušar, A. Vodopija

DIH4AI-Senso4S-E9

DIH4AI-Senso4S-E9

T. Tušar, A. Vodopija We collaborated with the Department of Knowledge Technologies and the Senso4s d.o.o. company in designing a...

Intelligent and environmentally friendly scheduling of field work – MF-Scheduler

Intelligent and environmentally friendly scheduling of field work – MF-Scheduler

B. Filipič, T. Tušar, A. Vodopija Scheduling of field work entails solving a demanding routing and scheduling problem. We assist...

PAST PROJECTS

Multi-objective optimization for artificial intelligence systems in industry

Multi-objective optimization for artificial intelligence systems in industry

B. Filipič, T. Tušar, A. Vodopija This is a bilateral, Slovenian-German project carried out together with the Institute for Data...

Machine vision quality control of molded plastic parts

Machine vision quality control of molded plastic parts

B. Filipič, E. Dovgan A project in collaboration with the MPT company

Improved planning of manufacturing processes for individualized tools

Improved planning of manufacturing processes for individualized tools

B. Filipič, E. Dovgan A project in collaboration with the Plamtex INT company

Multiobjective optimization for transparent tunnel design

Multiobjective optimization for transparent tunnel design

T. Tušar, E. Dovgan The goal of the TOPP (Transparent design of optimal underground connections for smart cities using artificial intelligence...

A computer system to schedule flexible offers for electricity production and consumption

A computer system to schedule flexible offers for electricity production and consumption

B. Filipič, T. Tušar In collaboration with the INEA company we developed optimization support for scheduling of flexible offers for...

Upgrade of the optimization system for steel continuous casting (KN3)

Upgrade of the optimization system for steel continuous casting (KN3)

B. Filipič. Zupančič, T. Tušar In this applied project, a simulation-based multiobjective optimization software was developed to support continuous casting...

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EVENTS

GECCO Job Market

GECCO Job Market

T. Tušar, B. Naujoks The Job Market is a GECCO event (organized every year since 2017) where people offering jobs...

Tutorial on Benchmarking Multiobjective Optimizers 2.0

Tutorial on Benchmarking Multiobjective Optimizers 2.0

D. Brockhoff, T. Tušar In this tutorial, we discuss the past and future of benchmarking multiobjective optimizers. In particular, we...

Tutorial on constraint handling in mutliobjective optimization

Tutorial on constraint handling in mutliobjective optimization

B. Filipič, A. Vodopija This tutorial provides an overview of the state of the art in constraint handling in multiobjective...

Tutorial on Visualization in Multiobjective Optimization

Tutorial on Visualization in Multiobjective Optimization

B. Filipič, T. Tušar This tutorial provides an overview of representative methods used in multiobjective optimization for visualizing: (1) individual...

Tutorial on Deploying Evolutionary Computation in Industry: Challenges and Lessons Learned

Tutorial on Deploying Evolutionary Computation in Industry: Challenges and Lessons Learned

B. Filipič This tutorial presents the challenges faced and lessons learned in designing evolutionary algorithms for industrial optimization problems that...

13th International Conference on Parallel Problem Solving from Nature

13th International Conference on Parallel Problem Solving from Nature

B. Filipič, T. Tušar The 13th International Conference on Parallel Problem Solving from Nature, PPSN 2014, was co-organized by the...

PEOPLE

Prof. Bogdan Filipič

Computational Intelligence Head

+386 1 477 3352

Andrejaana Andova, M.Sc.

Computational Intelligence

+386 1 477 3035

Dr. Tea Tušar

Computational Intelligence

+386 1 477 3462

Aljoša Vodopija, M.Sc.

Computational Intelligence

PUBLICATIONS

53 entries « 2 of 2 »

2017

Conference Papers

Dimo Brockhoff, Anne Auger, Nikolaus Hansen, Tea Tušar

Quantitative performance assessment of multiobjective optimizers : the average runtime attainment function Inproceedings

In: Heike Trautmann (Ed.): Evolutionary multi-criterion optimization : 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017 : proceedings, pp. str. 103-119, Springer, Cham, 2017.

BibTeX

Eric Medvet, Tea Tušar

The DU map : a visualization to gain insights into genotype-phenotype mapping and diversity Inproceedings

In: GECCO'17 companion : proceeding of the 2017 on Genetic and Evolutionary Computation Conference Companion, July 15-19, 2017 Berlin, Germany, pp. str. 1705-1712, ACM = Association for Computing Machinery, New York, 2017.

BibTeX | Links:

Tea Tušar, Nikolaus Hansen, Dimo Brockhoff

Anytime benchmarking of budget-dependent algorithms with the COCO platform Inproceedings

In: Mitja Luštrek, Rok Piltaver, Matjaž Gams (Ed.): Slovenska konferenca o umetni inteligenci : zbornik 20. mednarodne multikonference Informacijska družba - IS 2017, 9.-13. oktober 2017, [Ljubljana, Slovenia] : zvezek A = Slovenian Conference on Artificial Intelligence : proceedings of the 20th International Multiconference Information Society - IS 2017, 9th-13th October, 2017, Ljubljana, Slovenia : volume A, pp. str. 47-50, Institut Jožef Stefan, Ljubljana, 2017.

BibTeX

53 entries « 2 of 2 »