DNA Genetic Algorithm And Application Based On P Systems

In recent years,DNA-GA algorithms,which attracts many scholars’ attention,combinethe DNA encoding method with Genetic algorithm.It effectively overcomes GA’s limitationsuch as premature convergence, poor local search capability and binary Hamming cliffsproblems. How to design a more effective way to improve the performance of DNA-GAalgorithm has a strong theoretical and practical significance.In this work, a new DNA-GA algorithm based on P system (PDNA-GA) is proposed toimprove the performance of DNA-GA algorithms by combining the parallelism of P system inMembrane Computing. By studying the genetic algorithms, DNA computing and membranecomputing, a CAD program is designed to solve the model-designing problem.The performance of PDNA-GA in typical benchmark functions is studied.Theexperimental results demonstrate that the proposed algorithm can effectively yield the globaloptimum with high efficiency.The main points and innovations of this article are as follows:1. To improve the performance of DNA genetic algorithm, an adaptive mutation operatorand fitness function is designed to accelerate the speed of evolution.2. To improve the capability of parallelism, P system in Membrane Computing is comb-ined to the DNA-GA algorithm. And the average running time is apparently shortened.3. The algorithm proposed is combined with the CAD program and finally solve themodel-designing problem.