Слайд 1Solution Methods for Bilevel Optimization
Andrey Tin
A.Tin@soton.ac.uk
School of Mathematics
Supervisors: Dr Alain
B. Zemkoho, Professor Jörg Fliege
Слайд 2Overview
Define a bilevel problem and its general mathematical form
Discuss optimality
(KKT-type) conditions
Reformulate general bilevel problem as a system of equations
Consider
iterative (descent direction) methods applicable to solve this reformulation
Look at the numerical results of using Levenberg-Marquardt iterative method
Слайд 3Stackelberg Game (Bilevel problem)
Players: the Leader and the Follower
The Leader
is first to make a decision
Follower reacts optimally to Leader’s
decision
The payoff for the Leader depends on the follower’s reaction
Слайд 4Example
Taxation of a factory
Leader – government
Objectives: maximize profit and minimize
pollution
Follower – factory owner
Objectives: maximize profit
Слайд 5General structure of a Bilevel problem
Слайд 7Solution methods
Vertex enumeration in the context of Simplex method
Kuhn-Tucker approach
Penalty
approach
Extract gradient information from a lower objective function to compute
directional derivatives of an upper objective function
Слайд 9Value function reformulation
Слайд 10KKT for value function reformulation
Слайд 12KKT-type optimality conditions for Bilevel
Слайд 13Further Assumptions (for simpler version)
Слайд 14Simpler version of KKT-type conditions
Слайд 16Problems with differentiability
Fischer-Burmeister is not differentiable at 0
Слайд 18Simpler version with perturbed Fischer-Burmeister NCP functions
Слайд 23Singular Value Decomposition (SVD)
Слайд 28Convergence
Talk about starting point condition
Explain why it’s easier to prove
convergence for Newton and Gauss-Newton
Interest for future analysis
Слайд 30Plans for further work
6. Construct the own code for Levenberg-Marquardt
method in the context of solving bilevel problems within defined
reformulation.
7. Search for good starting point techniques for our problem. 8. Do the numerical calculations for the harder reformulation defined .
9. Code Newton method with pseudo-inverse.
10. Solve the problem assuming strict complementarity
11. Look at other solution methods.