Abstract
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. This paper generalizes uniform crossover to `non-uniform crossover' using `mask' vectors whose elements are real numbers qq[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. Simulation results show orders of magnitude improvement of this operator over two-point and uniform crossover. An appropriate schema theorem is also developed.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE Conference on Evolutionary Computation - Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 22-27 |
| Number of pages | 6 |
| Volume | 1 |
| State | Published - 1994 |
| Event | Proceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) - Orlando, FL, USA Duration: Jun 27 1994 → Jun 29 1994 |
Other
| Other | Proceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) |
|---|---|
| City | Orlando, FL, USA |
| Period | 6/27/94 → 6/29/94 |
ASJC Scopus subject areas
- General Engineering