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Many real-world optimization problems are dealing with constraints. The valid solution for constrained optimization problems (COP) lies somewhere in the feasible region which is a sub-set of the input-space. The borders of the feasible area are defined by one or many constraints. Existance of constraints makes the optimization problems more demanding. There are different approaches to handle the constraints but none of them can outperform all others for all different types of COPs. 


There are only a few constraint handlers which work on the basis of fixing a good "infeasible solution" and generating feasible solutions by using the information coming from the infeasible candidates. We proposed a new technique to repair infeasible solutions. The correspoding work was accepted as a paper in GECCO 2015. A talk about this work will be given in GECCO conference on 11-15 of July in Madrid.