Novel Optimization Method for Problems with Vastly Infeasible Search Spaces

Systems and methods may include identifying an input population of parent chromosome data structures, where each parent chromosome data structure provides a plurality of genes representative of variables in which associated values are permitted to evolve; selecting pairs of parent chromosome data structures from the input population of parent chromosome data structures; combining genes of each selected pair of parent chromosome data structures according to at least one evolutionary operator to generate a plurality of child chromosome data structures; evaluating the plurality of child chromosome data structures according to a plurality of constraint functions to generate a respective plurality of constraint function values for each child chromosome data structure, where the constraint functions define constraints on a feasible solution set; determining whether any of the plurality of child chromosome data structures are within the feasible solution set based upon the respective plurality of constraint violation function values.