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Industrial Optimization Research Group at University of Jyväskylä: Advancing Multiobjective Optimization and Decision Su

The Industrial Optimization Research Group at the University of Jyväskylä focuses on developing innovative methods and software for multiobjective optimization and decision support in various industrial applications. With a strong emphasis on interactive methods and robustness, the group also explores emerging areas such as data-driven decision support and explainable artificial intelligence.

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Industrial Optimization Research Group at University of Jyväskylä: Advancing Multiobjective Optimization and Decision Su

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  1. Optimointiryhmä Research Group in Industrial Optimization University of JyväskyläFaculty of Information Technology Kaisa Miettinen Prof. in Industrial Optimization kaisa.miettinen@jyu.fi http://www.mit.jyu.fi/optgroup/

  2. 1 professor Senior researcher Post docs Doctoral students FiDiPro 2015-2017 Often visitors (2 weeks – 6 moths) A lot of mobility National and international collaboration, so far in 2018 6 papers, 4 coll&proc papers, 1 special issue In 2017 10 visitors & 6 visits in 2009 7 conf talks Societies and networks International Society on MCDM, EMO Steering Group, Int. Soc. on Global Opt., EUROPT, FORS People

  3. Applications Primary areas of interest Software Methods Theory • Nonlinear multiobjective optimization • Multiple criteria decision making • Global optimization and evolutionary algorithms • Hybrid approaches • Software development • Industrial applications • Simulation-based and data-driven decision support Application fields

  4. Research topics I • Interactive multiobjective optimization • Method development including Nonconvex Pareto Navigator, family of NAUTILUS methods • DESDEO: http://www.mit.jyu.fi/optgroup/desdeo.html • Open source framework for interactive methods • Surrogate-assisted algorithms for computationally expensive problems • Scalarization-based: Surrogate-ASF, ANOVA-MOP • Evolutionary: K-RVEA, interactive K-RVEA • Robust multiobjective optimization • Interactive methods for communicating robustness to decision maker (uncertainty in variables or multipliers)

  5. Research topics II • Data-driven decision support with applications • Inventory management • Forest treatment planning • DUI punishing and project pricing • Industrial applications • Optimal shape design in tractor cabin • Emerging areas • Incorporating machine learning tools • Explainable artificial intelligence • DEMO - http://www.jyu.fi/demo • Thematic research area Decision Analytics utilizing Causal Models and Multiobjective Optimization

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