An improved differential evolution algorithm for binary CSPs

An improved differential evolution (IDE) algorithm is presented in this paper to solve binary constraint satisfaction problems (CSPs). To improve the performance IDE adjust the mutation rate F and the crossover rate CR dynamically with taking account of the different distribution of population. We use IDE to maintain the diversity of population and improve the global convergence ability. The experimental results show that our improved differential evolution algorithm is effective and efficient to solve binary CSPs.