On Zooming Genetic Algorithm and its Parallel Realization
变焦遗传算法及其并行实现研究

Genetic algorithm (GA) is widely applied to many fields due to its simplicity and adaptability. Generally, the search space and resolution of GA are limited by the string of GA, therefore, the solutions given by GA are usually local results. This paper analyzes the problems in GA and proposes the zooming GA(ZGA), which is suited to sequential and parallel computation. Strategies such as decoded factor, search center, fast mutation, etc. are adopted and the ZGA is realized on a wokrstation and transputers in sequential and parallel manners, respectively.