Benefits of Sexual Reproduction in Evolutionary Computation (original) (raw)
Evolutionary algorithms have proven to be highly successful for real world combinatorial optimization problems too complex to be handled by traditional algorithmic approaches. In stark contrast to their practical relevance, we only start to theoretically understand the stochastic processes which govern these optimization algorithms. The development of evolutionary algorithms was inspired by biological observations. In nature there seems to be an inherent advantage of sexual recombination compared to mere asexual reproduction. Thus many successful evolutionary algorithms in practice make use of recombination strategies. However, our theoretical understanding of crossover in evolutionary computation is very limited. This thesis studies the behavior of several evolutionary algorithms with a focus on the benefits of sexual reproduction. Two archetypical combinatorial optimization problems are the NP-hard Traveling Salesperson Problem (TSP) and the polynomial-time solvable all-pairs shor...
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