title: Modified differential evolution algorithm with onlooker bee operator for mixed discrete-continuous optimization.
abstract: For solving non-linear programming problems containing discrete and continuous variables, this article suggests two modified algorithms based on differential evolution (DE). The two proposed algorithms incorporate a novel random search strategy into DE/best/1 and DE/cur-to-best/1 respectively. Inspired by the artificial bee colony algorithm, the random search strategy overcomes the searching unbalance of DE/best/1 and DE/cur-to-best/1 by enhancing the global exploration capability of promising individuals. Two numerical experiments are given to test the two modified algorithms. Experiment 1 is conducted on the benchmark function set of CEC2005 in order to verify the effectiveness of the improved strategy. Experiment 2 is designed to optimize two mixed discrete-continuous problems to illustrate the competitiveness and the practicality of the proposed algorithms. In particular, the modified DE/cur-to-best/1 finds the new optima of two engineering optimization problems.
authors.affiliation: School of Computer Science and Technology, Wuhan University of Technology, Wuhan, 430070 People's Republic of China.
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Miao
authors.affiliation: School of Information and Mathematics, Yangtze University, Jingzhou, 434023 Hubei People's Republic of China.
authors.forename: Qinghua
authors.initials: Q
authors.lastname: Su
authors.affiliation: School of Information and Mathematics, Yangtze University, Jingzhou, 434023 Hubei People's Republic of China.
authors.forename: Zhongbo
authors.initials: Z
authors.lastname: Hu
authors.affiliation: School of Software, East China Jiaotong University, Nanchang, 330013 People's Republic of China.
authors.forename: Xuewen
authors.initials: X
authors.lastname: Xia
keywords: Artificial bee colony algorithm; Design of coil spring problem; Differential evolution Algorithm