An improved differential evolution for constrained optimization with dynamic constraint-handling mechanism

In this paper, an improved Differential Evolution (DE) with a self-adaptive strategy to determine the control parameters is proposed to solve constrained real-parameter optimization, combined with the dynamic constraint-handling mechanism. It is implemented by restating the single-objective constrained optimization as a set of single-objective unconstrained problems and dynamically assigning to the individual adaptively as its fitness, and the self-adaptive strategy of control parameters based on the intrinsic structure analysis of differential vectors is use to solve each unconstrained optimization problem individually. This approach is tested on a suit of test problems proposed for CEC2010 competition and special session on single objective constrained real-parameter optimization. The result indicates the combination of dynamic constraint-handling mechanism and self-adaptation of control parameters in DE will outperform using the former solely for constrained optimization.

[1]  Joni-Kristian Kämäräinen,et al.  Differential Evolution Training Algorithm for Feed-Forward Neural Networks , 2004, Neural Processing Letters.

[2]  Rainer Storn System design by constraint adaptation and differential evolution , 1999, IEEE Trans. Evol. Comput..

[3]  P. Suganthan,et al.  Problem Definitions and Evaluation Criteria for the CEC 2010 Competition on Constrained Real- Parameter Optimization , 2010 .

[4]  A. Kai Qin,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[5]  B. Babu,et al.  Differential evolution for multi-objective optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[6]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[7]  B. V. Babu,et al.  Multi-objective differential evolution (MODE) for optimization of supply chain planning and management , 2007, 2007 IEEE Congress on Evolutionary Computation.

[8]  Jing J. Liang,et al.  Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[9]  Swagatam Das,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[10]  Zhigang Shang,et al.  Differential evolution with dynamic constraint-handling mechanism , 2010, IEEE Congress on Evolutionary Computation.

[11]  Carlos A. Coello Coello,et al.  Modified Differential Evolution for Constrained Optimization , 2006, 2006 IEEE International Conference on Evolutionary Computation.