In this paper the population based incremental learning method is extended to a form of multiple traits for one gene to reflect pleiotropic and polygenic characters in natural evolved systems and the entropy of a pro...In this paper the population based incremental learning method is extended to a form of multiple traits for one gene to reflect pleiotropic and polygenic characters in natural evolved systems and the entropy of a probability distribution is used to decide the evolvability of the system. This method is used to solve a typical combinatorial optimization problem ─ the symmetric traveling salesman problem. Some results are better than the best existing algorithm of evolutionary algorithms for the problem.展开更多
文摘In this paper the population based incremental learning method is extended to a form of multiple traits for one gene to reflect pleiotropic and polygenic characters in natural evolved systems and the entropy of a probability distribution is used to decide the evolvability of the system. This method is used to solve a typical combinatorial optimization problem ─ the symmetric traveling salesman problem. Some results are better than the best existing algorithm of evolutionary algorithms for the problem.
