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Preference Robust Optimization with Multi-Attribute Quasi-Concave Choice Functions

2019-09-24
 

Academic Report


Title: Preference Robust Optimization with Multi-Attribute Quasi-Concave Choice Functions

Reporter: Prof. XU Huifu (university of southampton)

Time: Sept 25, 2019 (Wednesday) PM 16:00-17:00

Location: A1101# room, Innovation Park Building

Contact: Prof. ZHANG Liwei (tel:84708351-8097)

Abstract: Decision maker's preferences are captured by choice functions which are used to rank prospects. In thistalk, we study ambiguity in choice functions over a multi-attribute prospect space. Our main result is a robust preference model where the optimal decision is based on the worst-case choice function from an ambiguity set constructed through preference elicitation from pairwise comparisons of prospects. Differing from existing works, we focus on quasi-concave choice functions rather than concave functions enabling us to cover a wide range of utility/risk preference problems. Our robust choice function is non-decreasing and quasi-concave but not necessarily translation invariant, which is a key property of monetary risk measures. Our computational scheme is based on the support functions for the class of quasi-concave functions. We apply our technique to a security budget allocation problem and report preliminary experimental results.

The brief introduction to the reporter: Dr. Xu Huifu is currently a professor at the School of Mathematical Sciences, Southampton University. He received a master's degree in Computational Mathematics from Nanjing University in 1989 and a doctorate from Ballarat University in Australia in 1999. Professor Xu is an internationally renowned optimization expert. He has been engaged in continuous optimization research for more than 20 years. He has systematically studied stochastic programming and distributed robust optimization problems with equilibrium constraints, stochastic dominance constraints and so on, and has achieved a series of innovative results. Professor Xu has published more than 70 papers in international journals of operational research, such as Mathematical Programming, Mathematics of Operations Research, SIAM Journal on Optimization, etc. He has been invited to report at international high-level academic conferences for many times. He is currently the editor of international journals such as Computational Management Science.