A Hybrid Evolutionary Immune Algorithm for Multiobjective Optimization Problems

In recent years, multiobjective immune algorithms (MOIAs) have shown promising performance in solving multiobjective optimization problems (MOPs). However, basic MOIAs only use a single hypermutation operation to evolve individuals, which may induce some difficulties in tackling complicated MOPs. In this paper, we propose a novel hybrid evolutionary framework for MOIAs, in which the cloned individuals are divided into several subpopulations and then evolved using different evolutionary strategies. An example of this hybrid framework is implemented, in which simulated binary crossover and differential evolution with polynomial mutation are adopted. A fine-grained selection mechanism and a novel elitism sharing strategy are also adopted for performance enhancement. Various comparative experiments are conducted on 28 test MOPs and our empirical results validate the effectiveness and competitiveness of our proposed algorithm in solving MOPs of different types.

[1]  Dirk Thierens,et al.  The balance between proximity and diversity in multiobjective evolutionary algorithms , 2003, IEEE Trans. Evol. Comput..

[2]  Zhiwen Yu,et al.  Neighborhood Knowledge-Based Evolutionary Algorithm for Multiobjective Optimization Problems , 2011, IEEE Transactions on Evolutionary Computation.

[3]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[4]  Qingfu Zhang,et al.  Multiobjective optimization Test Instances for the CEC 2009 Special Session and Competition , 2009 .

[5]  Jürgen Branke,et al.  Learning Value Functions in Interactive Evolutionary Multiobjective Optimization , 2015, IEEE Transactions on Evolutionary Computation.

[6]  J. Tukey,et al.  Variations of Box Plots , 1978 .

[7]  Vincenzo Cutello,et al.  A Class of Pareto Archived Evolution Strategy Algorithms Using Immune Inspired Operators for Ab-Initio Protein Structure Prediction , 2005, EvoWorkshops.

[8]  Qiuzhen Lin,et al.  A novel hybrid multi-objective immune algorithm with adaptive differential evolution , 2015, Comput. Oper. Res..

[9]  P. Fleming,et al.  Convergence Acceleration Operator for Multiobjective Optimization , 2007, IEEE Transactions on Evolutionary Computation.

[10]  L.N. de Castro,et al.  An artificial immune network for multimodal function optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[11]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[12]  Marco Laumanns,et al.  Scalable Test Problems for Evolutionary Multiobjective Optimization , 2005, Evolutionary Multiobjective Optimization.

[13]  Yang Yang,et al.  A distributed cooperative coevolutionary algorithm for multiobjective optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[14]  Kalyanmoy Deb,et al.  A Hybrid Framework for Evolutionary Multi-Objective Optimization , 2013, IEEE Transactions on Evolutionary Computation.

[15]  Maoguo Gong,et al.  Multiobjective Immune Algorithm with Nondominated Neighbor-Based Selection , 2008, Evolutionary Computation.

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

[17]  Wang Hu,et al.  Adaptive Multiobjective Particle Swarm Optimization Based on Parallel Cell Coordinate System , 2015, IEEE Transactions on Evolutionary Computation.

[18]  Kay Chen Tan,et al.  Online Diversity Assessment in Evolutionary Multiobjective Optimization: A Geometrical Perspective , 2015, IEEE Transactions on Evolutionary Computation.

[19]  Qingfu Zhang,et al.  MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , 2007, IEEE Transactions on Evolutionary Computation.

[20]  Antonio J. Nebro,et al.  jMetal: A Java framework for multi-objective optimization , 2011, Adv. Eng. Softw..

[21]  Qingfu Zhang,et al.  Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition , 2014, IEEE Transactions on Evolutionary Computation.

[22]  Abdullah Al Mamun,et al.  An evolutionary artificial immune system for multi-objective optimization , 2008, Eur. J. Oper. Res..

[23]  Abdullah Al Mamun,et al.  Balancing exploration and exploitation with adaptive variation for evolutionary multi-objective optimization , 2009, Eur. J. Oper. Res..

[24]  Jun Zhang,et al.  An Evolutionary Algorithm with Double-Level Archives for Multiobjective Optimization , 2015, IEEE Transactions on Cybernetics.

[25]  Qingfu Zhang,et al.  Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II , 2009, IEEE Transactions on Evolutionary Computation.

[26]  Thomas Jansen,et al.  Reevaluating Immune-Inspired Hypermutations Using the Fixed Budget Perspective , 2014, IEEE Transactions on Evolutionary Computation.

[27]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.

[28]  Ye Tian,et al.  An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization , 2015, IEEE Transactions on Evolutionary Computation.

[29]  Carlos A. Coello Coello,et al.  Multiobjective Optimization Using Ideas from the Clonal Selection Principle , 2003, GECCO.

[30]  Sanghamitra Bandyopadhyay,et al.  An Algorithm for Many-Objective Optimization With Reduced Objective Computations: A Study in Differential Evolution , 2015, IEEE Transactions on Evolutionary Computation.

[31]  Zhuhong Zhang,et al.  Multiobjective optimization immune algorithm in dynamic environments and its application to greenhouse control , 2008, Appl. Soft Comput..

[32]  R. Lyndon While,et al.  A Scalable Multi-objective Test Problem Toolkit , 2005, EMO.

[33]  Qiuzhen Lin,et al.  A novel micro-population immune multiobjective optimization algorithm , 2013, Comput. Oper. Res..

[34]  Fabio Freschi,et al.  Multiobjective Optimization by a Modified Artificial Immune System Algorithm , 2005, ICARIS.

[35]  Maoguo Gong,et al.  Clonal Selection with Immune Dominance and Anergy Based Multiobjective Optimization , 2005, EMO.

[36]  Jun Zhang,et al.  Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches , 2015, ACM Comput. Surv..

[37]  Kay Chen Tan,et al.  A Competitive-Cooperative Coevolutionary Paradigm for Dynamic Multiobjective Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[38]  Henry Y. K. Lau,et al.  Immunity-based hybrid evolutionary algorithm for multi-objective optimization in global container repositioning , 2008, Eng. Appl. Artif. Intell..

[39]  Xianpeng Wang,et al.  A Hybrid Multiobjective Evolutionary Algorithm for Multiobjective Optimization Problems , 2013, IEEE Transactions on Evolutionary Computation.

[40]  Thomas Stützle,et al.  Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms , 2016, IEEE Transactions on Evolutionary Computation.

[41]  Jiannong Cao,et al.  Multiple Populations for Multiple Objectives: A Coevolutionary Technique for Solving Multiobjective Optimization Problems , 2013, IEEE Transactions on Cybernetics.

[42]  Qiuzhen Lin,et al.  A double-module immune algorithm for multi-objective optimization problems , 2015, Appl. Soft Comput..

[43]  Maoguo Gong,et al.  Clonal Selection Algorithm for Dynamic Multiobjective Optimization , 2005, CIS.

[44]  Zhi-Hua Hu,et al.  A multiobjective immune algorithm based on a multiple-affinity model , 2010, Eur. J. Oper. Res..

[45]  Zhuhong Zhang,et al.  Immune optimization algorithm for constrained nonlinear multiobjective optimization problems , 2007, Appl. Soft Comput..

[46]  Zhen Ji,et al.  A hybrid immune multiobjective optimization algorithm , 2010, Eur. J. Oper. Res..

[47]  Hisao Ishibuchi,et al.  Diversity Improvement by Non-Geometric Binary Crossover in Evolutionary Multiobjective Optimization , 2010, IEEE Transactions on Evolutionary Computation.

[48]  R. K. Ursem.  Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[49]  Ki-Baek Lee,et al.  Multiobjective Particle Swarm Optimization With Preference-Based Sort and Its Application to Path Following Footstep Optimization for Humanoid Robots , 2013, IEEE Transactions on Evolutionary Computation.

[50]  Fabio Freschi,et al.  VIS: An artificial immune network for multi-objective optimization , 2006 .

[51]  Jun Wang,et al.  WBMOAIS: A novel artificial immune system for multiobjective optimization , 2010, Comput. Oper. Res..

[52]  Kiyoshi Tanaka,et al.  Computational Cost Reduction of Nondominated Sorting Using the M-Front , 2015, IEEE Transactions on Evolutionary Computation.

[53]  Carlos A. Coello Coello,et al.  Solving Multiobjective Optimization Problems Using an Artificial Immune System , 2005, Genetic Programming and Evolvable Machines.

[54]  DebK.,et al.  A fast and elitist multiobjective genetic algorithm , 2002 .

[55]  P. Hajela,et al.  Immune network simulations in multicriterion design , 1999 .

[56]  Abdullah Al Mamun,et al.  Multi-Objective Optimization with Estimation of Distribution Algorithm in a Noisy Environment , 2013, Evolutionary Computation.

[57]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[58]  Enrique Alba,et al.  AbYSS: Adapting Scatter Search to Multiobjective Optimization , 2008, IEEE Transactions on Evolutionary Computation.

[59]  Fang Liu,et al.  A Novel Immune Clonal Algorithm for MO Problems , 2012, IEEE Transactions on Evolutionary Computation.

[60]  Enrique Alba,et al.  SMPSO: A new PSO-based metaheuristic for multi-objective optimization , 2009, 2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making(MCDM).

[61]  F. Azuaje.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[62]  Kalyanmoy Deb,et al.  Self-Adaptive Genetic Algorithms with Simulated Binary Crossover , 2001, Evolutionary Computation.

[63]  Qingfu Zhang,et al.  Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model , 2010, IEEE Transactions on Evolutionary Computation.

[64]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..