An evolutionary programming algorithm for continuous global optimization

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{YaowenYang:2005:EJOR,

• author = "Yaowen Yang and Jianfeng Xu and Chee Kiong Soh",
• title = "An evolutionary programming algorithm for continuous global optimization",
• journal = "European Journal of Operational Research",
• year = "2006",
• volume = "168",
• pages = "354--369",
• email = "cywyang@ntu.edu.sg",
• URL = "http://www.elsevier.com/locate/ejor",
• number = "2",
• month = "16 " # jan,
• note = "Feature Cluster on Mathematical Finance and Risk Management",
• keywords = "genetic algorithms, genetic programming, Evolutionary computations, Evolutionary programming, Global optimisation, Simulated annealing",
• DOI = "doi:10.1016/j.ejor.2004.05.007",
• abstract = "Evolutionary computations are very effective at performing global search (in probability), however, the speed of convergence could be slow. This paper presents an evolutionary programming algorithm combined with macro-mutation (MM), local linear bisection search (LBS) and crossover operators for global optimisation. The MM operator is designed to explore the whole search space and the LBS operator to exploit the neighbourhood of the solution. Simulated annealing is adopted to prevent premature convergence. The performance of the proposed algorithm is assessed by numerical experiments on 12 benchmark problems. Combined with MM, the effectiveness of various local search operators is also studied.",
• notes = "School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore

  Science direct gives authors as Yao Wen Yang, Jian Feng Xu, Chee Kiong Soh.",

}

Genetic Programming entries for Yaowen Yang Jianfeng Xu Chee Kiong Soh

Citations