Modern Gray Box Optimization makes it possible to construct new forms of Genetic Algorithms that do not use random mutation or random recombination. For certain classes of NP Hard problems (ranging from MAXSAT to QUBO to Machine Scheduling to the Traveling Salesman Problem), it is possible to exactly compute the location of improving moves, sometimes in constant time.

New results show that there are additional decompositions that can be exploited by intelligent recombination operators such as “Partition Crossover” (PX). Very new results
show that the local optima exposed by recombination also display periodicity in Fourier space and there exists higher level relationships between these local optima in the search space. New theoretical results also show why offspring are more likely than not to also be local optima in the full space. This allows partition crossover to directly “tunnel” between local optima, moving directly from local optimum to local optimum. Recent theoretical results also show that the local optima for combinatorial problems are largely arranged in a hierarchically organized lattice structure. The tutorial will also highlight connections between Evolutionary Algorithms and Quantum Computing.