Hi, in theory it is possible. You can have a look to the following link:

http://bilevel.org/

If you need to solve a bilevel problem I suggest you turn to the theoretically valid tools in that field - the tools within meta-heuristics are not at all meant to be used in such a difficult context. In fact it is at least as difficult to solve a bilevel problem as a hard integer/combinatorial optimization problem.

Heuristics are of course possible to use, but you have the added complexity in that the lower-level problem needs - eventually - to be solved correctly, as you are otherwise not even feasible. That is a rather serous limitation of meta-heuristics in general.

Firstly, it is required to analyze the problem correctly, second it is required to formulate the conceptual model of complete problem. Thirdly, it is required to break down the conceptual pattern in a multi-level structure, the one that could, in particular, consist on a centralized, scattered disperse or hierarchical structure Each one of the tasks of the defined structure has to be correctly identified, that is to say defined all the relationships that appear in each model. Only in this moment become necessary to solve each tasks of the lower and higher levels and the conciliaton task among them to satisfy the interests of the complete system. Only at this moment you can build the algorithms to solve the tasks that are part of the overall problem. I am attaching you a work where it is described the ways to analyze and to decompose the original problem and algorithms appear to solve the complete task. Best wishes,

it is absolutely possible, you can check this book on your question:

1- Metaheuristics for Bi-level Optimization

http://link.springer.com/book/10.1007%2F978-3-642-37838-6

2- Sinha, A., Malo, P., & Deb, K. (2017). Evolutionary Bilevel Optimization: An Introduction and Recent Advances. In Recent Advances in Evolutionary Multi-objective Optimization (pp. 71-103). Springer International Publishing.

for GA, these papers have answered your question:

1- Genetic algorithm based approach to bi-level linear programming

http://archive.numdam.org/ARCHIVE/RO/RO_1994__28_1/RO_1994__28_1_1_0/RO_1994__28_1_1_0.pdf

2- A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem–A case study on supply chain model

http://www.sciencedirect.com/science/article/pii/S0307904X11000655

3- I also recommend this work:

A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms, MIT, 2016

https://arxiv.org/pdf/1401.1905.pdf

Corus, D., Lehre, P. K., Neumann, F., & Pourhassan, M. (2016). A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms. Evolutionary computation, 24(1), 183-203.