Decomposition Multi-Objective Optimisation and Decision-Making: When Traditional Optimisation Meet Modern Meta-heuristics and Artificial Intelligence

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• Dr Ke Li (UKRI Future Leaders Fellow and Senior Lecturer, Computer Science, University of Exeter)
• Monday 09 December 2019, 11:00-12:00
• Computer Science, The Sloman Lounge (UG).

If you have a question about this talk, please contact Hector Basevi.

Host: Prof Jon Rowe (J.E.Rowe@cs.bham.ac.uk)

Abstract: Evolutionary multi-objective optimization (EMO) has been a major research topic in the field of evolutionary computation for many years. It has been generally accepted that combination of evolutionary algorithms and traditional optimization methods should be a next generation multi-objective optimization solver. As the name suggests, the basic idea of the decomposition-based technique is to transform the original complex problem into simplified subproblem(s) so as to facilitate the optimization. Decomposition methods have been well used and studied in traditional multi-objective optimization.

In this talk, I will start with a gentle introduction of a simple and general decomposition-based EMO algorithm framework, dubbed MOEA /D. Then, I will introduce some progress in MOEA /D happened in my lab. Afterwards, I will introduce some more emergent topic on multi-criterion decision-making and interactive EMO . At the end, I will overview some other ongoing projects in my lab.

Website: https://cola-laboratory.github.io/

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

This talk is included in these lists:

• Artificial Intelligence and Natural Computation seminars
• Computer Science Departmental Series
• Computer Science Distinguished Seminars
• Computer Science, The Sloman Lounge (UG)
• computer sience

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