Improved genetic algorithm inspired by biological evolution

Soft Computing

Volumn 11, Issue 10, 2007, Pages 923-941

  Kumar, P ^a   Gospodaric, D ^a   Bauer, P ^b  

^a Trimerics GmbH   (Germany)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Genetic algorithms; Multi objective optimization; Mutations

Indexed keywords

ADAPTIVE ALGORITHMS; GENE ENCODING; MULTIOBJECTIVE OPTIMIZATION; PARETO PRINCIPLE;

MUTATION; MUTATION OPERATORS; PARETO-OPTIMAL SOLUTIONS;

GENETIC ALGORITHMS;

EID: 34248681270     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-006-0143-x     Document Type: Article

References (32)

1. Aguirre H, Tanaka K (2005) Selection, drift, recombination, and mutation in multiobjective evolutionary algorithms on scalable MNK-Landscapes. Evolutionary multi-criterion optimization. 3rd international conference, EMO 2005, Lecture notes in computer science, vol 3410, pp 355-369
2. Bagley JD (1967) The behavior of adaptive systems which employ genetic and correlation algorithms. PhD Thesis, University of Michigan
3. Brizuela CA, Aceves R (2003) Experimental genetic operators analysis for the multi-objective permutation flowshop. volutionary multi-criterion optimization. In: 2nd international conference, EMO 2003, vol 2632, pp 578-592
4. Chan TM, Man KF, Tang KS, Kwong S (2005) A jumping gene algorithm for multiobjective resource management in wideband CDMA systems. Comput J 48:749-768
5. Coello CAC (1993) A micro-genetic algorithm for multiobjective optimization. Lecture Notes in Computer Science
6. Coello CAC, Veldhuizen V et al. (2002) Evolutionary algorithms for solving multi-objective problems. Kluwer, New York
7. Coello CAC, PulidoD GT, Lechuga MS (2004) Handling multiple objectives with particle swarm optimization. IEEE Trans Evol Comput 8:256-279
8. Darwin C, Huxely J (1859) Origin of Species. Signet Classics
9. Deb K (1999) Multiobjective genetic algorithms: Problem difficulties and construction of test problems. Evol Comput 7:205-230
10. Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Chichester
11. Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast elitist nondominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Proceedings of the parallel problem solving from nature VI(PPSN-VI), pp 849-858
12. Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Proceedings of the 5th international conference on genetic algorithms
13. Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley Publishing Company, Reading
14. Holland JH (1975) Adaptation in natural and artificial systems. MIT Press, Cambridge
15. Horn J, Nafploitis N, Goldberg DE (1994) A niched Paretogenetic algorithm for multi-objective optimization. In: Proceedings of the 1st IEEE conference on evolutionary computation
16. Kita H, Yabumoto Y, Mori N, Nishikawa Y (1996) Multi-objective optimization by means of the thermodynamical genetic algorithm. In: Parallel problem solving from nature - PPSN IV. Voigt H-M, Ebeling W, Rechenberg I, Schwefel H-P, (eds) Springer Berlin Heidelberg New York, pp 504-512
17. Knowles J, Corne D (2002) On metrics for comparing nondominated sets. Congress on Evolutionary Computation CEC, 2002 Piscataway
18. Knowles JD, Corne DW (2000) Approximating the nondominated front using the Pareto archived evolution strategy. Evol Comput 8:149-172
19. Knowles J, Thiele L, Zitzler E (2006) A tutorial on the performance assessment of stochastic multiobjective optimizers no. 214. Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich
20. Kursawe F (1991) A variant of evolution strategies for vector optimization. Lecture Notes in Computer Science. In: Schwefel HP, Männer R, (eds) Springer Berlin Heidelberg New York, vol 496. pp 193-197
21. Li WH (1993) Molecular evolution. Sinauer, Sunderland, MA
22. Nei M (1986) Molecular evolutionary genetics. Columbia University Press, New York
23. Schott JR (1995) Fault tolerant design using single and multicriteria genetic algorithm optimization. M.S. Thesis, Dept. Aeronautics and Astronautics, MIT, Cambridge
24. Srinivas N, Deb K (1994) Multi-objective function optimization using non-dominated sorting genetic algorithms. Evol Comput J 3:221-248
25. Tan KC, Lee TH, Khor EF (2001) Evolutionary algorithm with dynamic population size and local exploration for multiobjective optimization. IEEE Trans Evol Comput 5:565-586
26. Van Veldhuizen DA, Lamont GB (1998) Multiobjective evolutionary algorithm research: A history and analysis. Dept. Elec. Comput. Eng., Graduate School of Eng., Air Force Inst. Technol., Tech. Rep-98-03
27. Van Veldhuizen DA, Lamont GB (2000) On measuring multiobjective evolutionary algorithm performance. In: Congress on evolutionary computation (CEC 2000), vol 1, pp 204-211
28. Zitzler E, Thiele L (1998) Multiobjective optimization using evolutionary algorithms-A comparitive study. Parallel Probl Solv Nat 5:292-301
29. Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans Evol Comput 3:257-271
30. Zitzler E, Deb K, Thiele L (2000a) Multiobjective genetic algorithms: problem difficulties and construction of test problems. Evol Comput 7:205-230
31. Zitzler E, Deb K, Thiele L (2000b) Comparison of multiobjective evolutionary algorithms: Empirical results. Evol Comput 8:173-195
32. Zitzler E, Thiele L, Laumanns M, Fonseca CM, Fonseca VG (2003) Performance assessment of multiobjective optimizers: An analysis and review. IEEE Trans Evol Comput 7:117-132