Knowledge-based nonuniform crossover

One-point, two-point and k-point crossover can be viewed as special cases of uniform crossover, where genetic material is chosen each locus of either parent with equal probability (G. Syswerda, 1989). The paper generalizes uniform crossover to “non-uniform crossover” using “mask” vectors whose elements are real numbers ∈[0, 1], representing problem-specific knowledge that improves performance by biasing the selection of alleles from either parent. This knowledge based non-uniform crossover (KNUX) is applied to two NP optimization problems: graph partitioning and soft-decision decoding of linear block codes (H.S. Maini, 1993). Simulation results show orders of magnitude improvement of this operator over two-point and uniform crossover. An appropriate schema theorem is also developed