A Hybrid Evolutionary Algorithm for Mixed-Integer Nonlinear Bilevel Programming Problems

This paper presents a hybrid evolutionary algorithm to solve mixed-integer nonlinear bilevel programming problems, in which integer decision variables are controlled by an upper-level decision maker and real-value (continuous) decision variables are controlled by a lower-level decision maker. This hybrid evolutionary algorithm contains the mutation operator used in the differential evolution, the crossover operator as which the orthogonal experimental design serves, and the migration operator to keep the population's diversity. Simulation results show that the proposed algorithm can find global optimal solutions with less computation burden.