Dissertation title Interactive methods for multiobjective robust optimization

Dissertation title: Interactive methods for multiobjective robust optimization Supervisors: Prof. Kaisa Miettinen and Dr. Karthik Sindhya. Founded by University of Jyväskylä Key research questions: – How applicable are the robustness concepts in decision making for practical problems? – How to support a decision maker in finding the final solution for problems under uncertainty? Contribution: – Bridging theory and practice of multiobjective robust optimization. – Providing necessary tools to support a decision maker in multiobjective robust optimization.

Papers and manuscripts – Yue Zhou-Kangas, Kaisa Miettinen, and Karthik Sindhya. Solving Multiobjective Optimization Problems with Decision Uncertainty: an Interactive approach. Journal of Business Economics, to appear, doi: 10. 1007/s 11573 -018 -0900 -1, 2018. – Yue Zhou-Kangas, Kaisa Miettinen, and Karthik Sindhya. Interactive Multiobjective Robust Optimization with NIMBUS. In Proceedings of the Clausthal-Göttingen International Workshop on Simulation Science, to appear, 2018. – Yue Zhou-Kangas and Kaisa Miettinen. A simple indicator based evolutionary algorithm for set-based minmax robustness. Parallel Problem Solving from Nature - PPSN XV. PPSN 2018, Proceedings. Springer, to appear, 2018. – Yue Zhou-Kangas and Anita Schöbel. The price of multiobjective robustness analyzing solution sets to uncertain multiobjective optimization problems. Manuscript. – Yue Zhou-Kangas and Kaisa Miettinen. Decision making in multiobjective optimization problems under uncertainty: balancing between robustness and quality. Manuscript. Plans towards completion – Thesis should go to the pre-evaluators after the appointment of Faculty of IT. – Planed defense: somewhere in late Autumn this year.