关键词: 离散差分骨干粒子群优化, 分布估计, 无约束二进制二次规划问题, 组合优化

Abstract: Particle Swarm Optimization（PSO） and Differential Evolution（DE） are two latest optimization techniques.These algorithms have been very successful in solving the global continuous optimization，but their applications to combinatorial optimization have been rather limited and are not as effective as in global continuous optimization.Recently，a Differential Barebones PSO（DBPSO） is also proposed for global continuous optimization.Firstly，a discrete DBPSO is proposed for combinatorial optimization，and then the Estimation of Distribution Algorithm（EDA） is incorporated into the discrete DBPSO to improve its performance.The proposed discrete DBPSO algorithm based on EDA combines global statistical information extracted by EDA with local evolution information obtained by discrete DBPSO to create promising solutions.The results of experiment show that the EDA can significantly improve the performance of the discrete DBPSO.

Key words: discrete differential barebones Particle Swarm Optimization（PSO）, estimation of distribution, unconstrained binary quadratic programming problem, combinatorial optimization