A self-adaptive cloud co-evolution genetic algorithm for parameter identification of advanced manufacturing mode diffusion

作者：Chaogai Xue; Yu Sheng; Haiwang Cao^*

来源：Journal of Software Engineering, 2016, 10(4): 448-456.

DOI：10.3923/jse.2016.448.456

• Adaptive genetic algorithms
• Advanced manufacturing
• Co-evolution
• Competitive strategy
• Differential Evolution
• Global search ability
• Parameter identification model
• Parameter identification problems

Background: To solve the parameter identification of a multiple advanced-manufacturing-mode competitive diffusion (ACD), this study proposes an improved self-adaptive cloud co-evolution genetic a lgorithm (ISCCGA) combining a cloud differential evolution model with competitive strategies. Materials and Methods: First, the multiple-ACD model is described and the parameter identification model is formulated. Then, to solve the parameter identification of mult iple-ACD model, ISCCGA is proposed in which differential evolut ion of a cloud model and competitive strategies are introduced into the crossover operator to improve the convergence speed and global search ability. In addition, the co-evolution and mutation probabilities are improved to implement nonlinear adaptive adjustment. And then optimal parameters are obtained. Results: Finally, the influences of parameters on the algorithm are inv estigated and the validity of ISCCGA is verified. Conclusion: This experimental results show that ISCCGA is more efficient f or parameter identification problem in terms of accuracy and convergence than simple genetic, adaptive genetic and co-evolution adaptive genetic algorithms.

• 出版日期2016
• 单位郑州大学