Evolutionary Bilevel Optimization

IEEE World Congress on Computational Intelligence 2016

July 25-29, 2016, Vancouver, Canada

Bilevel optimization problems are special kind of optimization problems that involve two levels of optimization, namely upper level and lower level. The hierarchical structure of the problem requires that every feasible solution to the upper level problem should satisfy the optimality conditions of the lower level problem. Such a requirement makes bilevel optimization problems difficult to solve. These problems are commonly found in many practical problem solving tasks, which include optimal control, process optimization, game-playing strategy development, transportation problems, coordination of multi-divisional firms, machine learning and others. Due to the computation expense and other difficulties involved in handling such problems, they are often handled using approximate solution procedures. There is a need for theoretical as well as methodological advancements to handle such problems efficiently.

Congress on Evolutionary Computation (CEC) at WCCI 2016 in Vancouver, Canada will give an opportunity to researchers and practitioners to discuss and exchange ideas for handling bilevel problems, which have yet not been widely explored by the evolutionary computation community. The special session on Bilevel Optimization will bring together researchers working on the following topics:

• Evolutionary algorithms for bilevel optimization problems
• Evolutionary algorithms for multi-objective bilevel optimization problems
• Approximate procedures to handle bilevel optimization problems
• Hybrid approaches to handle bilevel optimization problems
• Theoretical results on bilevel optimization problems
• Bilevel Application Problems
• Hierarchical decision making

Organizers

Dr. Ankur Sinha (asinha [at] iima.ac.in)
Indian Institute of Management, Ahmedabad, India

Prof. Kalyanmoy Deb (kdeb [at] egr.msu.edu)
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.