Research

Research Topics

Below is a summary of my main research interests, highlighting representative publications. For a comprehensive list of my publications, please refer to the publications page.

Constrained Multiobjective Optimization

My research explores how constraints impact multiobjective optimization problems. Specifically, I focus on:

Understanding Multiobjective Optimization Problems

I am interested in improving the understanding of multiobjective optimization problems, particularly by:

Benchmarking Methodology and Problems

In collaboration with colleagues from the RandOpt Team at Inria, France, we actively advance benchmarking practices and the development of new benchmark optimization problems. This includes:

In addition, through other international collaborations, we have introduced suites of game-based benchmark problems (see also this dedicated website) and explored a methodology for creating a diverse problem suite.

Visualization Techniques

Visualization techniques play a central role in my research, offering clear insights into the properties of optimization problems and the internal dynamics of optimization algorithms. I have worked on:

Real-World Applications

Over the years, I have tackled a variety of real-world optimization problems:

Scheduling for Renewable Energy Integration

Engineering and Manufacturing

Transport and Logistics

Other Domains

Additionally, we have identified properties of real-world optimization problems with a survey (see also this dedicated website for the results).

Multiobjective Optimization Algorithms

I have contributed to developing and analyzing multiobjective optimization algorithms based on differential evolution, notably:

  • The DEMO (Differential Evolution for Multiobjective Optimization) algorithm
  • GP-DEMO (Gaussian-Process-based DEMO) for tackling problems with computationally expensive solution evaluations
  • BBDEMO (Black-Box DEMO), inspired by the BBDE and COMO-CMA-ES algorithms, made for solving mixed-integer problems

Projects

To see a list of current and past projects, please see the Computational Intelligence group website.

Software

I have contributed to the development of the following software tools and packages:

The COCO Platform

COCO (Comparing Continuous Optimizers) is a software platform for a systematic and sound comparison of continuous and mixed optimization algorithms.

The moarchiving Library

The moarchiving Python library implements a multi-objective non-dominated archive for 2, 3 or 4 objectives, providing easy and fast access to multiple hypervolume indicators.

The OPI Tool

OPI (Optimization Problem Inspector) is a tool for analysis of industrial optimization problems and their solutions.

Talks

Tutorials

  • Benchmarking Multobjective Optimizers 2.0
    Tutorial with Dimo Brockoff at GECCO 2021, GECCO 2022, EMO 2023 and GECCO 2023

    Bibtex

     
    @inproceedings{Brockhoff21TutorialGECCO,
  author       = {Dimo Brockhoff and Tea Tu{\v s}ar},
  title        = {Benchmarking multiobjective optimizers 2.0},
  booktitle    = {{GECCO} '21: Genetic and Evolutionary Computation Conference, Companion Volume},
  pages        = {664--668},
  publisher    = {{ACM}},
  year         = {2021},
  doi          = {10.1145/3449726.3461421}
}
@inproceedings{Brockhoff22TutorialGECCO,
  author       = {Dimo Brockhoff and Tea Tu{\v s}ar},
  title        = {{GECCO} 2022 Tutorial on benchmarking multiobjective optimizers 2.0},
  booktitle    = {{GECCO} '22: Genetic and Evolutionary Computation Conference, Companion Volume},
  pages        = {1269--1309},
  publisher    = {{ACM}},
  year         = {2022},
  doi          = {10.1145/3520304.3533635}
}
@inproceedings{Brockhoff23TutorialGECCO,
  author       = {Dimo Brockhoff and Tea Tu{\v s}ar},
  title        = {{GECCO} 2023 Tutorial on Benchmarking Multiobjective Optimizers 2.0},
  booktitle    = {Companion Proceedings of the Conference on Genetic and Evolutionary Computation, {GECCO} 2023},
  pages        = {1183--1212},
  publisher    = {{ACM}},
  year         = {2023},
  doi          = {10.1145/3583133.3595060}
}

  • Visualization in Multiobjective Optimization
    Tutorial with Bogdan Filipič at GECCO 2016, CEC 2017, GECCO 2018, GECCO 2019 and GECCO 2020
    See the supplementary material page for additional resources

    Bibtex

     
    @inproceedings{Filipic16Tutorial,
  author       = {Bogdan Filipi{\v c} and Tea Tu{\v s}ar},
  title        = {Visualization in Multiobjective Optimization},
  booktitle    = {Companion Material Proceedings of the Genetic and Evolutionary Computation Conference, {GECCO} 2016},
  pages        = {735--751},
  publisher    = {{ACM}},
  year         = {2016},
  doi          = {10.1145/2908961.2926994}
}
@inproceedings{Filipic18Tutorial,
  author       = {Bogdan Filipi{\v c} and Tea Tu{\v s}ar},
  title        = {Visualization in Multiobjective Optimization},
  booktitle    = {Companion Proceedings of the Genetic and Evolutionary Computation Conference, {GECCO} 2018},
  pages        = {858--879},
  publisher    = {{ACM}},
  year         = {2018},
  doi          = {10.1145/3205651.3207891}
}
@inproceedings{Filipic19Tutorial,
  author       = {Bogdan Filipi{\v c} and Tea Tu{\v s}ar},
  title        = {Visualization in Multiobjective Optimization},
  booktitle    = {Companion Proceedings of the Genetic and Evolutionary Computation Conference, {GECCO} 2019},
  pages        = {951--974},
  publisher    = {{ACM}},
  year         = {2019},
  doi          = {10.1145/3319619.3323374}
}
@inproceedings{Filipic20Tutorial,
  author       = {Bogdan Filipi{\v c} and Tea Tu{\v s}ar},
  title        = {Visualization in Multiobjective Optimization},
  booktitle    = {{GECCO} '20: Genetic and Evolutionary Computation Conference, Companion Volume},
  pages        = {775--800},
  publisher    = {{ACM}},
  year         = {2020},
  doi          = {10.1145/3377929.3389867}
}

Awards

  • Taras award for successful collaboration of the economy and the research and development environment in the field of innovation, development and technology, Industrial Forum IRT 2023, Portorož, Slovenia
    Members of the Department of Intelligent Systems (Tea Tušar, Aljoša Vodopija, Jordan Cork, Bogdan Filipič), Department of Computer Systems (Peter Korošec) and the company Mahle Electric Drives Slovenija, d.o.o.: Development of an electric motor for the automotive industry with an innovative simulation-based optimization procedure

  • Best poster award at EvoStar 2023, Brno, Czechia
    Andrejaana Andova, Tobias Benecke, Harald Ludwig, Tea Tušar: Towards constructing a suite of multi-objective optimization problems with diverse landscapes

  • Best paper award at the Slovenian Conference on Artificial Intelligence, 26th International Multiconference Information Society, IS 2023, Ljubljana, Slovenia
    Tea Tušar, Peter Korošec, Bogdan Filipič: A multi-step evaluation process in electric motor design

  • Second place at the XPRIZE Pandemic Response Challenge, 2021
    Team JSI vs. COVID

  • Best paper award at the XV International Conference ETAI 2021, Skopje, Northern Macedonia
    Nina Reščič, Vito Janko, David Susič, Carlo De Masi, Aljoša Vodopija, Matej Marinko, Tea Tušar, Erik Dovgan, Matej Cigale, Anton Gradišek, Matjaž Gams, Mitja Luštrek: Finding efficient intervention plans against COVID-19

  • Best paper award at Human-Computer Interaction in Information Society, 23rd International Multiconference Information Society, IS 2020, Ljubljana, Slovenia
    Tea Tušar: Interactive visualization of the Slovenian budget with the Sankey diagram