Evolutionary Bilevel Optimization

Genetic and Evolutionary Computation Conference (GECCO) 2013

July 6-10 2013, Amsterdam, Netherlands

The relevance of bilevel optimization problems has been amply recognized by researchers and practitioners alike. Bilevel optimization problems differ from ordinary optimization problems, as it has two levels of optimization tasks, the upper level or outer optimization task and the lower level or inner optimization task. The lower level optimization task appears as a constraint to the upper level optimization task, such that only an optimal solution to the lower level problem may be a feasible candidate to the upper level optimization problem. This caveat makes bilevel optimization a challenging task, which demands immense computational resources to successfully solve even smaller instances of the problem.

Bilevel optimization often appears as a leader-follower problem in the fields of game theory and economics. These problems are also found in other practical problem solving tasks which include optimal control, process optimization, transportation problems etc. Bilevel problems have been of interest to the classical optimization community as well, who have provided approaches with strict assumptions capable of handling simpler versions of these problems. However, most of the approaches are rendered inapplicable as soon as the complexity of the problem rises. There is a need for theoretical as well as methodological advancements to handle bilevel problems efficiently.

Organizers

Dr. Ankur Sinha
Aalto University School of Business, Helsinki, Finland

Dr. Pekka Malo
Aalto University School of Business, Helsinki, Finland

Dr. Kalyanmoy Deb
Michigan State University, East Lansing, MI, USA

Keywords

Bilevel Optimization, Bilevel Multi-objective Optimization, Evolutionary Algorithms, Multi-Criteria Decision Making, Theory on Bilevel Programming, Hierarchical Decision Making, Bilevel Applications, Hybrid Algorithms.