Reflected Adaptive Differential Evolution with Two External Archives for Large-Scale Global Optimization

JADE is an adaptive scheme of nature inspired algorithm, Differential Evolution (DE). It performed considerably improved on a set of well-studied benchmark test problems. In this paper, we evaluate the performance of new JADE with two external archives to deal with unconstrained continuous large-scale global optimization problems labeled as Reflected Adaptive Differential Evolution with Two External Archives (RJADE/TA). The only archive of JADE stores failed solutions. In contrast, the proposed second archive stores superior solutions at regular intervals of the optimization process to avoid premature convergence towards local optima. The superior solutions which are sent to the archive are reflected by new potential solutions. At the end of the search process, the best solution is selected from the second archive and the current population. The performance of RJADE/TA algorithm is then extensively evaluated on two test beds. At first on 28 latest benchmark functions constructed for the 2013 Congress on Evolutionary Computation special session. Secondly on ten benchmark problems from CEC2010 Special Session and Competition on Large-Scale Global Optimization. Experimental results demonstrated a very competitive perfor-mance of the algorithm.

[1]  Janez Brest,et al.  Some Improvements of the Self-Adaptive jDE Algorithm , 2014, 2014 IEEE Symposium on Differential Evolution (SDE).

[2]  Ponnuthurai N. Suganthan,et al.  Recent advances in differential evolution - An updated survey , 2016, Swarm Evol. Comput..

[3]  B. D. Bunday,et al.  Basic optimisation methods , 1985, Mathematical Gazette.

[4]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[5]  Fei Peng,et al.  Multi-start JADE with knowledge transfer for numerical optimization , 2009, IEEE Congress on Evolutionary Computation.

[6]  Alex S. Fukunaga,et al.  Improving the search performance of SHADE using linear population size reduction , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[7]  Jason Sheng-Hong Tsai,et al.  A self-optimization approach for L-SHADE incorporated with eigenvector-based crossover and successful-parent-selecting framework on CEC 2015 benchmark set , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

[8]  Yuping Wang,et al.  Variable grouping based differential evolution using an auxiliary function for large scale global optimization , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

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

[10]  Lixin Tang,et al.  Differential Evolution With an Individual-Dependent Mechanism , 2015, IEEE Transactions on Evolutionary Computation.

[11]  Bingyan Zhao,et al.  Hybrid-Coding Binary Differential Evolution Algorithm with Application to 0-1 Knapsack Problems , 2008, 2008 International Conference on Computer Science and Software Engineering.

[12]  A. Kai Qin,et al.  Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.

[13]  M.M.A. Salama,et al.  Opposition-Based Differential Evolution , 2008, IEEE Transactions on Evolutionary Computation.

[14]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[15]  M. M. Ali,et al.  A numerical study of some modified differential evolution algorithms , 2006, Eur. J. Oper. Res..

[16]  Muhammad Asif Jan,et al.  Centroid-based Initialized JADE for global optimization , 2011, 2011 3rd Computer Science and Electronic Engineering Conference (CEEC).

[17]  Liang Changyong.  Hybrid binary differential evolution algorithm for 0-1 knapsack problem , 2010 .

[18]  Xin Yao,et al.  Large scale evolutionary optimization using cooperative coevolution , 2008, Inf. Sci..

[19]  Carlos A. Coello Coello,et al.  An analysis of the automatic adaptation of the crossover rate in differential evolution , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[20]  A. Abraham,et al.  Simplex Differential Evolution , 2009 .

[21]  Si-Yu Xia,et al.  Self-adaptive differential evolution with local search chains for real-parameter single-objective optimization , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[22]  Ville Tirronen,et al.  Recent advances in differential evolution: a survey and experimental analysis , 2010, Artificial Intelligence Review.

[23]  Ilpo Poikolainen,et al.  Cluster-Based Population Initialization for differential evolution frameworks , 2015, Inf. Sci..

[24]  Mehmet Fatih Tasgetiren,et al.  Differential evolution algorithm with ensemble of parameters and mutation strategies , 2011, Appl. Soft Comput..

[25]  Janez Brest,et al.  Real Parameter Single Objective Optimization using self-adaptive differential evolution algorithm with more strategies , 2013, 2013 IEEE Congress on Evolutionary Computation.

[26]  Hitoshi Iba,et al.  Accelerating Differential Evolution Using an Adaptive Local Search , 2008, IEEE Transactions on Evolutionary Computation.

[27]  Jouni Lampinen,et al.  A mutation and crossover adaptation mechanism for differential evolution algorithm , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[28]  Xin Yao,et al.  Self-adaptive differential evolution with neighborhood search , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[29]  Janez Brest,et al.  Structured Population Size Reduction Differential Evolution with Multiple Mutation Strategies on CEC 2013 real parameter optimization , 2013, 2013 IEEE Congress on Evolutionary Computation.

[30]  Qingfu Zhang,et al.  Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters , 2011, IEEE Transactions on Evolutionary Computation.

[31]  Xiaodong Li,et al.  Benchmark Functions for the CEC'2010 Special Session and Competition on Large-Scale , 2009 .

[32]  Liang Gao,et al.  An effective improvement of JADE for real-parameter optimization , 2013, 2013 Sixth International Conference on Advanced Computational Intelligence (ICACI).

[33]  Arthur C. Sanderson,et al.  JADE: Adaptive Differential Evolution With Optional External Archive , 2009, IEEE Transactions on Evolutionary Computation.

[34]  Alex S. Fukunaga,et al.  Success-history based parameter adaptation for Differential Evolution , 2013, 2013 IEEE Congress on Evolutionary Computation.

[35]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[36]  Janez Brest,et al.  SELF-ADAPTIVE DIFFERENTIAL EVOLUTION WITH SQP LOCAL SEARCH , 2008 .

[37]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[38]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[39]  Vijander Singh,et al.  An Improved Differential Evolution Algorithm for Real Parameter Optimization Problems , 2009 .