Abstract:

Concerning that the general hybrid genetic algorithms cannot give attention to both effectiveness and efficiency, a new hybrid genetic algorithm using two-dimensional variable neighborhood coding named VNHGA was proposed. Firstly, the traditional binary coding method was replaced by a new coding method, which was designed to separate coding and synchronous inheritance for individuals. Secondly, the traditional mutation operator was replaced by a new stable mutation operator to improve efficiency. VNHGA was tested by optimization problem of multi-dimensional functions. It was verified that, after adopting the new coding method, features with more effectiveness and less efficiency were maintained when using "Baldwin effect" relative to using "Lamarckian evolution" as embedding strategy. After introducing the stable mutation operator, effectiveness was maintained and efficiency was improved at the same time, and the running time was shortened about half of before. VNHGA was also compared with other two modified hybrid genetic algorithms to exhibit its advantages. The results indicate that VNHGA is both effective and efficient, and it can be used to solve optimization problems.