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Volumn , Issue , 2008, Pages 20-42

Multi-objective particles swarm optimization approaches

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EID: 79952363152     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-498-9.ch002     Document Type: Chapter
Times cited : (62)

References (56)
  • 1
    • 24344505520 scopus 로고    scopus 로고
    • A MOPSO algorithm based exclusively on Pareto dominance concepts
    • Springer-Verlag
    • Alvarez-Benitez, J. E., Everson, R. M., & Fieldsend, J. E. (2005). A MOPSO algorithm based exclusively on Pareto dominance concepts. Lecture notes in computer science (Vol. 3410, pp. 459-473). Springer-Verlag.
    • (2005) Lecture Notes in Computer Science , vol.3410 , pp. 459-473
    • Alvarez-Benitez, J.E.1    Everson, R.M.2    Fieldsend, J.E.3
  • 2
    • 35248815986 scopus 로고    scopus 로고
    • The maximin fitness function; Multi-objective city and regional planning
    • Springer-Verlag
    • Balling, R. (2003). The maximin fitness function; Multi-objective city and regional planning. Lecture notes in computer science (Vol. 2632, pp. 1-15). Springer-Verlag.
    • (2003) Lecture Notes in Computer Science , vol.2632 , pp. 1-15
    • Balling, R.1
  • 5
    • 4344689783 scopus 로고    scopus 로고
    • Autonomous agent response learning by a multi-species particle swarm optimization
    • In, IEEE Service Center
    • Chow, C.-K. & Tsui, H.-T. (2004). Autonomous agent response learning by a multi-species particle swarm optimization. In Proceedings of the 2004 IEEE Congress on Evolutionary Computation (pp. 778-785). IEEE Service Center.
    • (2004) Proceedings of the 2004 IEEE Congress on Evolutionary Computation , pp. 778-785
    • Chow, C.-K.1    Tsui, H.-T.2
  • 6
    • 0036464756 scopus 로고    scopus 로고
    • The particle swarm-explosion, stability, and convergence in a multidimensional complex space
    • Clerc, M. & Kennedy, J. (2002). The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput., 6(1), 58-73.
    • (2002) IEEE Trans. Evol. Comput , vol.6 , Issue.1 , pp. 58-73
    • Clerc, M.1    Kennedy, J.2
  • 10
    • 0033185714 scopus 로고    scopus 로고
    • Multi-objective genetic algorithms: Problem difficulties and construction of test problems
    • Deb, K. (1999). Multi-objective genetic algorithms: Problem difficulties and construction of test problems. Evolutionary Computation, 7(3), 205-230.
    • (1999) Evolutionary Computation , vol.7 , Issue.3 , pp. 205-230
    • Deb, K.1
  • 11
    • 0002284602 scopus 로고
    • An investigation of niche and species formation in genetic function optimization
    • In, Morgan Kaufmann Publishing
    • Deb, K., & Goldberg, D. E. (1989). An investigation of niche and species formation in genetic function optimization. In Proceedings of the 3rd International Conference on Genetic Algorithms (pp. 42-50). Morgan Kaufmann Publishing.
    • (1989) Proceedings of the 3rd International Conference on Genetic Algorithms , pp. 42-50
    • Deb, K.1    Goldberg, D.E.2
  • 12
    • 0036530772 scopus 로고    scopus 로고
    • A fast and elitist multi-objective genetic algorithm: NSGA-II
    • 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.
    • (2002) IEEE Trans. Evol. Comput , vol.6 , Issue.2 , pp. 182-197
    • Deb, K.1    Pratap, A.2    Agarwal, S.3    Meyarivan, T.4
  • 14
    • 84947807745 scopus 로고    scopus 로고
    • Comparison between genetic algorithms and particle swarm optimization
    • In V. W. Porto et al. (Eds.), Springer
    • Eberhart, R. C. & Shi, Y. (1998). Comparison between genetic algorithms and particle swarm optimization. In V. W. Porto et al. (Eds.), Evolutionary programming: Vol. VII (pp. 611-616). Springer.
    • (1998) Evolutionary Programming , pp. 611-616
    • Eberhart, R.C.1    Shi, Y.2
  • 15
    • 84931452896 scopus 로고    scopus 로고
    • The niched Pareto genetic algorithm 2 applied to the design of groundwater remediation systems
    • Springer-Verlag
    • Erickson, M., Mayer, A., & Horn, J. (2001). The niched Pareto genetic algorithm 2 applied to the design of groundwater remediation systems. Lecture notes in computer science (Vol. 1993, pp. 681-695). Springer-Verlag.
    • (2001) Lecture Notes in Computer Science , vol.1993 , pp. 681-695
    • Erickson, M.1    Mayer, A.2    Horn, J.3
  • 16
    • 0037803427 scopus 로고    scopus 로고
    • Using unconstrained elite archives for multi-objective optimization
    • Fieldsend, J. E., Everson, R. M., & Singh, S. (2003). Using unconstrained elite archives for multi-objective optimization. IEEE Trans. Evol. Comp., 7(3), 305-323.
    • (2003) IEEE Trans. Evol. Comp , vol.7 , Issue.3 , pp. 305-323
    • Fieldsend, J.E.1    Everson, R.M.2    Singh, S.3
  • 17
    • 3142781424 scopus 로고    scopus 로고
    • A multiobjective algorithm based upon particle swarm optimisation, An efficient data structure and turbulence
    • In, Birmingham, UK
    • Fieldsend, J. E. & Singh, S. (2002). A multiobjective algorithm based upon particle swarm optimisation, An efficient data structure and turbulence. In Proceedings of the 2002 UK Work-shop on Computational Intelligence (pp. 34-44). Birmingham, UK.
    • (2002) Proceedings of the 2002 UK Work-shop on Computational Intelligence , pp. 34-44
    • Fieldsend, J.E.1    Singh, S.2
  • 20
    • 22044450246 scopus 로고    scopus 로고
    • A particle swarm optimization-based method for multi-objective design optimizations
    • Ho, S. L., Yang, S., Ni, G., Lo, E. W. C., & Wong, H. C. (2005). A particle swarm optimization-based method for multi-objective design optimizations. IEEE Trans. Magnetics, 41(5), 1756-1759.
    • (2005) IEEE Trans. Magnetics , vol.41 , Issue.5 , pp. 1756-1759
    • Ho, S.L.1    Yang, S.2    Ni, G.3    Lo, E.W.C.4    Wong, H.C.5
  • 22
    • 84901470581 scopus 로고    scopus 로고
    • Multi-objective optimization using dynamic neighborhood particle swarm optimization
    • In, IEEE Service Center
    • Hu, X. & Eberhart, R. (2002). Multi-objective optimization using dynamic neighborhood particle swarm optimization. In Proceedings of the 2002 IEEE Congress Evolutionary Compututation (pp. 1677-1681). IEEE Service Center.
    • (2002) Proceedings of the 2002 IEEE Congress Evolutionary Compututation , pp. 1677-1681
    • Hu, X.1    Eberhart, R.2
  • 23
  • 24
    • 33749540149 scopus 로고    scopus 로고
    • A smart particle swarm optimization algorithm for multiobjective problems
    • 4115, Springer-Verlag
    • Huo, X. H., Shen, L. C., Zhu, H. Y. (2006). A smart particle swarm optimization algorithm for multiobjective problems. Lecture notes in computer science (Vol. 4115, pp. 72-80). Springer-Verlag.
    • (2006) Lecture Notes in Computer Science , pp. 72-80
    • Huo, X.H.1    Shen, L.C.2    Zhu, H.Y.3
  • 25
    • 35048901195 scopus 로고    scopus 로고
    • A hierarchical particle swarm optimizer for dynamic optimization problems
    • Springer-Verlag
    • Janson, S. & Middendorf, M. (2004). A hierarchical particle swarm optimizer for dynamic optimization problems. Lecture notes in computer science (Vol. 3005, pp. 513-524). Springer-Verlag.
    • (2004) Lecture Notes in Computer Science , vol.3005 , pp. 513
    • Janson, S.1    Middendorf, M.2
  • 26
    • 0142172455 scopus 로고    scopus 로고
    • Evolutionary dynamic weighted aggregation for multi-objective optimization: Why does it work and how?
    • In, San Francisco, CA
    • Jin, Y., Olhofer, M., & Sendhoff, B. (2001). Evolutionary dynamic weighted aggregation for multi-objective optimization: Why does it work and how? In Proceedings of the GECCO 2001 Conference (pp. 1042-1049), San Francisco, CA.
    • (2001) Proceedings of the GECCO 2001 Conference , pp. 1042-1049
    • Jin, Y.1    Olhofer, M.2    Sendhoff, B.3
  • 27
    • 84899047533 scopus 로고    scopus 로고
    • Small worlds and mega-minds: Effects of neighborhood topology on particle swarm performance
    • In, IEEE Press
    • Kennedy, J. (1999). Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. In Proceedings of the IEEE Congress Evolutionary Computation (pp. 1931-1938). IEEE Press.
    • (1999) Proceedings of the IEEE Congress Evolutionary Computation , pp. 1931-1938
    • Kennedy, J.1
  • 30
    • 0034199912 scopus 로고    scopus 로고
    • Approximating the nondominated front using the Pareto archived evolution strategy
    • Knowles, J D. & Corne, D. W. (2000). Approximating the nondominated front using the Pareto archived evolution strategy. Evolutionary computation, 8(2), 149-172.
    • (2000) Evolutionary Computation , vol.8 , Issue.2 , pp. 149-172
    • Knowles, J.D.1    Corne, D.W.2
  • 31
    • 35248851524 scopus 로고    scopus 로고
    • A non-dominated sorting particle swarm optimizer for multi-objective optimization
    • Springer-Verlag
    • Li, X. (2003). A non-dominated sorting particle swarm optimizer for multi-objective optimization. Lecture notes in computer science, Vol. 2723 (pp. 37-48). Springer-Verlag.
    • (2003) Lecture Notes in Computer Science , vol.2723 , pp. 37-48
    • Li, X.1
  • 32
    • 35048841216 scopus 로고    scopus 로고
    • Better spread and convergence: Particle swarm multi-objective optimization using the maximin fitness function
    • Springer-Verlag
    • Li, X. (2004). Better spread and convergence: Particle swarm multi-objective optimization using the maximin fitness function. Lecture notes in computer science, Vol. 3102 (pp. 117-128). Springer-Verlag.
    • (2004) Lecture Notes in Computer Science , vol.3102 , pp. 117-128
    • Li, X.1
  • 33
    • 33044501377 scopus 로고    scopus 로고
    • Adaptive weighted particle swarm optimisation for multi-objective optimal design of alloy steels
    • Springer
    • Mahfouf, M., Chen, M.-Y., & Linkens, D. A. (2004). Adaptive weighted particle swarm optimisation for multi-objective optimal design of alloy steels. Lecture notes in computer science (Vol. 3242, pp. 762-771). Springer.
    • (2004) Lecture Notes in Computer Science , vol.3242 , pp. 762-771
    • Mahfouf, M.1    Chen, M.-Y.2    Linkens, D.A.3
  • 34
    • 84942162725 scopus 로고    scopus 로고
    • Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)
    • In, IEEE Service Center
    • Mostaghim, S. & Teich, J. (2003a). Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO). In Proceedings of the 2003 IEEE Swarm Intelligence Symposium (pp. 26-33). IEEE Service Center.
    • (2003) Proceedings of the 2003 IEEE Swarm Intelligence Symposium , pp. 26-33
    • Mostaghim, S.1    Teich, J.2
  • 36
    • 4344649636 scopus 로고    scopus 로고
    • Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization
    • In, IEEE Press
    • Mostaghim, S. & Teich, J. (2004). Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization. In Proceedings of the IEEE 2004 Congress on Evolutionary Computation (pp. 1404-1411). IEEE Press.
    • (2004) Proceedings of the IEEE 2004 Congress on Evolutionary Computation , pp. 1404-1411
    • Mostaghim, S.1    Teich, J.2
  • 37
    • 33750228992 scopus 로고    scopus 로고
    • About selecting the personal best in multi-objective particle swarm optimization
    • Springer
    • Mostaghim, S. & Teich, J. (2006). About selecting the personal best in multi-objective particle swarm optimization. Lecture notes in computer science (Vol. 4193, pp. 523-532). Springer.
    • (2006) Lecture Notes in Computer Science , vol.4193 , pp. 523-532
    • Mostaghim, S.1    Teich, J.2
  • 39
    • 0344291226 scopus 로고    scopus 로고
    • Recent approaches to global optimization problems through particle swarm optimization
    • Parsopoulos, K. E. & Vrahatis, M. N. (2002a). Recent approaches to global optimization problems through particle swarm optimization. Natural Computing, 1(2-3), 235-306.
    • (2002) Natural Computing , vol.1 , Issue.2-3 , pp. 235-306
    • Parsopoulos, K.E.1    Vrahatis, M.N.2
  • 41
    • 3142669892 scopus 로고    scopus 로고
    • On the computation of all global minimizers through particle swarm optimization
    • Parsopoulos, K. E. & Vrahatis, M. N. (2004). On the computation of all global minimizers through particle swarm optimization. IEEE Transactions on Evolutionary Computation, 8(3), 211-224.
    • (2004) IEEE Transactions on Evolutionary Computation , vol.8 , Issue.3 , pp. 211-224
    • Parsopoulos, K.E.1    Vrahatis, M.N.2
  • 42
    • 34247548801 scopus 로고    scopus 로고
    • Parameter selection and adaptation in unified particle swarm optimization
    • Parsopoulos, K. E. & Vrahatis, M. N. (2007). Parameter selection and adaptation in unified particle swarm optimization. Mathematical and Computer Modelling, 46(1-2), 198-213.
    • (2007) Mathematical and Computer Modelling , vol.46 , Issue.1-2 , pp. 198-213
    • Parsopoulos, K.E.1    Vrahatis, M.N.2
  • 43
    • 32444449874 scopus 로고    scopus 로고
    • An effecive use of crowding distance in multi-objective particle swarm optimization
    • In, ACM Press
    • Raquel, C. R. & Naval, P. C., Jr. (2005). An effecive use of crowding distance in multi-objective particle swarm optimization. In Proceedings of the GECCO 2005 (pp. 257-264). ACM Press.
    • (2005) Proceedings of the GECCO 2005 , pp. 257-264
    • Raquel, C.R.1    Naval Jr., P.C.2
  • 44
    • 0036522301 scopus 로고    scopus 로고
    • A swarm metaphor for multi-objective design optimization
    • Ray, T. & Liew, K. M. (2002). A swarm metaphor for multi-objective design optimization. Engineering Optimization, 34(2), 141-153.
    • (2002) Engineering Optimization , vol.34 , Issue.2 , pp. 141-153
    • Ray, T.1    Liew, K.M.2
  • 45
    • 24344480582 scopus 로고    scopus 로고
    • Improving PSO-based multi-objective optimisation using crowding, mutation and ε-dominance
    • Springer-Verlag
    • Reyes-Sierra, M. & Coello, C. A. (2005). Improving PSO-based multi-objective optimisation using crowding, mutation and ε-dominance. Lecture notes in computer science (Vol. 3410, pp. 505-519). Springer-Verlag.
    • (2005) Lecture Notes in Computer Science , vol.3410 , pp. 505-519
    • Reyes-Sierra, M.1    Coello, C.A.2
  • 48
    • 27144464848 scopus 로고    scopus 로고
    • Particle swarm optimization and fitness sharing to solve multi-objective optimization problems
    • In, IEEE Service Center
    • Salazar Lechuga, M. & Rowe, J. E. (2005). Particle swarm optimization and fitness sharing to solve multi-objective optimization problems. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation (pp. 1204-1211). IEEE Service Center.
    • (2005) Proceedings of the 2005 IEEE Congress on Evolutionary Computation , pp. 1204-1211
    • Salazar Lechuga, M.1    Rowe, J.E.2
  • 50
    • 0000599395 scopus 로고
    • Multiple objective optimisation with vector evaluated genetic algorithm
    • In, Morgan Kaufmann Publishers
    • Schaffer, J. D. (1985). Multiple objective optimisation with vector evaluated genetic algorithm. In Proceedings of the 1st International Conference on Genetic Algorithms (pp. 93-100). Morgan Kaufmann Publishers.
    • (1985) Proceedings of the 1st International Conference on Genetic Algorithms , pp. 93-100
    • Schaffer, J.D.1
  • 51
    • 0000852513 scopus 로고
    • Multi-objective optimization using nondominated sorting in genetic algorithms
    • Srinivas, N. & Deb, K. (1994). Multi-objective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2(3), 221-248.
    • (1994) Evolutionary Computation , vol.2 , Issue.3 , pp. 221-248
    • Srinivas, N.1    Deb, K.2
  • 52
    • 84901478115 scopus 로고    scopus 로고
    • Particle swarm inspired evolutionary algorithm (PS-EA) for multi-objective optimization problem
    • In, IEEE Press
    • Srinivasan, D. & Seow, T. H. (2003). Particle swarm inspired evolutionary algorithm (PS-EA) for multi-objective optimization problem. In Proceedings of the IEEE 2003 Congress on Evolutionary Computation (pp. 2292-2297). IEEE Press.
    • (2003) Proceedings of the IEEE 2003 Congress on Evolutionary Computation , pp. 2292-2297
    • Srinivasan, D.1    Seow, T.H.2
  • 53
    • 35048830890 scopus 로고    scopus 로고
    • Using clustering techniques to improve the performance of a particle swarm optimizer
    • Springer
    • Toscano Pulido, G., & Coello, C. A. (2004). Using clustering techniques to improve the performance of a particle swarm optimizer. Lecture notes in computer science (Vol. 3102, pp. 225-237). Springer.
    • (2004) Lecture Notes in Computer Science , vol.3102 , pp. 225-237
    • Toscano Pulido, G.1    Coello, C.A.2
  • 55
    • 28244477574 scopus 로고    scopus 로고
    • Determining generator contributions to transmission system using parallel vector evaluated particle swarm optimization
    • Vlachogiannis, J. G. & Lee, K. Y. (2005). Determining generator contributions to transmission system using parallel vector evaluated particle swarm optimization. IEEE Transactions on Power Systems, 20(4), 1765-1774.
    • (2005) IEEE Transactions on Power Systems , vol.20 , Issue.4 , pp. 1765-1774
    • Vlachogiannis, J.G.1    Lee, K.Y.2
  • 56
    • 0033318858 scopus 로고    scopus 로고
    • Multi-objective evolutionary algorithms: A comparative case study and the strength Pareto approach
    • Zitzler, E. & Thiele, L. (1999). Multi-objective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput., 3(4), 257-271.
    • (1999) IEEE Trans. Evol. Comput , vol.3 , Issue.4 , pp. 257-271
    • Zitzler, E.1    Thiele, L.2


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