Chaos-based multi-objective immune algorithm with a fine-grained selection mechanism

Soft Computing

Volumn 15, Issue 7, 2011, Pages 1273-1288

  Chen, Jianyong ^a   Lin, Qiuzhen ^a   Ji, Zhen ^a  

^a SHENZHEN UNIVERSITY   (China)

Author keywords

Chaos; Chaotic mutation operator; Immune algorithm; Multi objective algorithm

Indexed keywords

BENCHMARK FUNCTIONS; CHAOTIC MUTATION OPERATOR; CHAOTIC SEQUENCE; CLONAL SELECTION PRINCIPLE; DIVERSITY ESTIMATION; ERGODICS; IMMUNE ALGORITHM; MULTI OBJECTIVE; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; MULTI-OBJECTIVE ALGORITHM; MUTATION OPERATORS; NONDOMINATED SOLUTIONS; NSGA-II; PARETO-OPTIMAL FRONT; POLYNOMIAL MUTATION; SELECTION MECHANISM; SIMULATION RESULT; STEP SIZE; STOCHASTIC PROPERTIES;

HIERARCHICAL SYSTEMS; MATHEMATICAL OPERATORS; MULTIOBJECTIVE OPTIMIZATION;

EVOLUTIONARY ALGORITHMS;

EID: 79958071303     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-010-0661-4     Document Type: Article

References (33)

1. Campelo F, Guimaraes FG, Igarashi H (2007) Overview of artificial immune systems for multi-objective optimization. In Obayashi S, Deb K, Poloni C, Hiroyasu T, Murata T (eds) Evolutionary multi-criterion optimization, 4th international conference, EMO 2007. Lecture Notes in Computer Science, vol 4403. Springer, Matshushima, Japan, pp 937-951.
2. Chua LO, Yao Y (1990) Generating randomness from chaos and constructing chaos with desired randomness. Int J Circuit Theory Appl 18: 215-240.
3. Coelho LdS, Alotto P (2008) Multiobjective electromagnetic optimization based on a nondominated sorting genetic approach with a chaotic crossover operator. IEEE Trans Magn 44(6): 1078-1081.
4. Coelho LdS, Mariani VC (2009) Chaotic artificial immune approach applied to economic dispatch of electric energy using thermal units. Chaos Soliton Fractals 40(5): 2376-2383.
5. Corne DW, Jerram NR, Knowles JD, Oates MJ (2001) PESA-II: region-based selection in evolutionary multi-objective optimization. In: Proceedings of the genetic and evolutionary computation conference, pp 283-290.
6. Cutello V, Narzisi G, Nicosia G (2005) A class of pareto archived evolution strategy algorithms using immune inspired operators for ab initio protein structure prediction. Third European workshop on evolutionary computation and bioinformatics, LNCS, vol 3449. Lausanne, Switzerland. Springer, pp 54-63.
7. De Castro LN, Von Zuben FJ (2002) Learning and optimization using the clonal selection. IEEE Trans Evol Comput 6(3): 239-251.
8. Deb K, Beyer HG (2001) Self-adaptive genetic algorithms with simulated binary crossover. Evol Comput 9(2): 197-221.
9. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2): 182-197.
10. Deb K, Thiele L, Laumanns M, Zitzler E (2005) Scalable test problems for evolutionary multi-objective optimization. In: Evolutionary multiobjective optimization in advanced information and knowledge processing series. Springer, Berlin, pp 105-145.
11. Du HF, Gong MG, Liu RC, Jiao LC (2005) Adaptive chaos clonal evolutionary programming algorithm. Sci China Ser F 48(5): 579-595.
12. Fonseca CM, Fleming PJ (1995) An overview of evolutionary algorithms in multiobjective optimization. Evol Comput 3(1): 1-16.
13. Fonseca CM, Flemming PJ (1998) Multiobjective optimization and multiple constraint handling with evolutionary algorithms. Part II: application example. IEEE Trans Syst Man Cybern Part A Syst Hum 28(1): 38-47.
14. Freschi F, Coello Coello CA, Repetto M (2009) Multiobjective optimization and artificial immune systems: a review. In Mo H (ed) Handbook of research on artificial immune systems and natural computing: applying complex adaptive technologies. Medical Information Science Reference, Hershey, pp 1-21.
15. Gong MG, Jiao LC, Du HF, Bo L (2008) Multi-objective Immune algorithm with nondominated neighbor-based selection. Evol Comput (MIT Press) 16(2): 225-255.
16. Halavati R, Shouraki SB (2009) Symbiotic artificial immune system. Soft Comput 13(6): 565-575.
17. Jia LV (2007) Study on chaos immune network algorithm for multimodal function optimization. In: Proceedings of fourth international conference on fuzzy systems and knowledge discovery, vol 3, pp 684-688.
18. Knowles JD, Corne DW (2000) Approximating the non-dominated front using the pareto archived evolution strategy. Evol Comput 2: 149-172.
19. Kursawe F (1990) A variant of evolution strategies for vector optimization. In: Parallel problem solving from nature. 1st Workshop, PPSN I. Lecture notes in computer science, vol 496. Springer, Berlin, pp 193-197.
20. Liu J, Cai Z, Liu J (2000) A novel genetic algorithm preventing premature convergence by chaos operator. J Cent South Univ Technol 7(2): 100-103.
21. Lu H, Zhichun M (2008) A clonal chaos adjustment algorithm for multi-modal function optimization. In: Proceedings of the 27 Chinese control conference, pp 98-102.
22. Qi R, Qian F, Li S, Wang Z (2006) Chaos-genetic algorithm for multiobjective optimization. In: Proceedings of sixth world congress on intelligent control and automation, pp 1563-1566.
23. Schaffer JD (1987) Multiple objective optimization with vector evaluated genetic algorithms. In: Proceedings of first international conference on genetic algorithms, pp 93-100.
24. van den Berg HA (2009) Design principles of adaptive cellular immunity for artificial immune systems. Soft Comput 13(11): 1073-1080.
25. Van Veldhuizen DA, Lamont GB (1998) Multiobjective evolutionary algorithm research: a history and analysis. Tech. Rep. TR-98-03, Department of Electrical and Computer Engineering, Graduate School of Engineering, Air Force Institute of Technology.
26. Wang XL, Mahfouf M (2006) ACSAMO: an adaptive multiobjective optimization algorithm using the clonal selection principle. In: 2nd European symposium on nature-inspired smart information systems, pp 1-12.
27. Yang DX, Li G, Cheng GD (2007) On the efficiency of chaos optimization algorithms for global optimization. Chaos Soliton Fractals 34(4): 1366-1375.
28. Yue X, Abraham A, Chi ZX, Hao YY, Mo HW (2007) Artificial immune system inspired behavior-based anti-spam filter. Soft Comput 11(8): 729-740.
29. Zhang Z (2007) Immune optimization algorithm for constrained nonlinear multiobjective optimization problems. Appl Soft Comput 7(3): 840-857.
30. Zhao CM, You XH, Cheng SX (1995) Digital generator of chaos sequence and its application in communication. J Southeast Univ China 25(4): 137-142.
31. Zhou A, Jin Y, Zhang Q, Sendhoff B, Tsang E (2006) Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion. In: Proceedings of 2006 conference on evolutionary computation, pp 892-899.
32. Zitzler E, Deb K, Thiele L (2000) Comparison of multiobjective evolutionary algorithms: empirical results. Evol Comput 8(2): 173-195.
33. Zitzler E, Laumanns M, Thiele L (2002) SPEA2: improving the strength pareto evolutionary algorithm. In: Evolutionary methods for design, optimization and control with applications to industrial problems. Athens, Greece, pp 95-100.