References
- [1]
- V. S. Amaral, P. B. Assunção and D. R. Souza. A Partially Derivative-Free Proximal Method for Composite Multiobjective Optimization in the Hölder Setting (2026), arXiv:2508.20071 [math.OC]. ↩1 ↩2
- [2]
- M. Ansary and G. Panda. A modified Quasi-Newton method for vector optimization problem. Optimization 64, 2289–2306 (2015). ↩1 ↩2
- [3]
- [4]
- [5]
- D. Dumitrescu, C. Grosan and M. Oltean. A New Evolutionary Approach for Multiobjective Optimization. Studia Universitatis Babeș-Bolyai Informatica XLV, 51–67 (2000). ↩1 ↩2
- [6]
- K. Deb, L. Thiele, M. Laumanns and E. Zitzler. Scalable Test Problems for Evolutionary Multiobjective Optimization. In: Evolutionary Multiobjective Optimization: Theoretical Advances and Applications, edited by A. Abraham, L. Jain and R. Goldberg (Springer London, London, 2005); pp. 105–145. ↩1 ↩2
- [7]
- A. Farhang-Mehr and S. Azarm. Diversity assessment of Pareto optimal solution sets: an entropy approach. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), Vol. 1 (2002); p. 723–728 vol.1. ↩1 ↩2
- [8]
- M. Farina. A neural network based generalized response surface multiobjective evolutionary algorithm. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), Vol. 1 (2002); p. 956–961 vol.1. ↩1 ↩2
- [9]
- [10]
- J. Fliege, L. M. Drummond and B. F. Svaiter. Newton's Method for Multiobjective Optimization. SIAM Journal on Optimization 20, 602–626 (2009). ↩1 ↩2 ↩3 ↩4 ↩5 ↩6
- [11]
- C. M. Fonseca and P. J. Fleming. An Overview of Evolutionary Algorithms in Multiobjective Optimization. Evolutionary Computation 3, 1–16 (1995). ↩1 ↩2
- [12]
- [13]
- K. Ikeda, H. Kita and S. Kobayashi. Failure of Pareto-based MOEAs: does non-dominated really mean near to optimal? In: Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546), Vol. 2 (2001); pp. 957–962. ↩1 ↩2
- [14]
- H. Ishibuchi and T. Murata. A multi-objective genetic local search algorithm and its application to flowshop scheduling. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 28, 392–403 (1998). ↩1 ↩2
- [15]
- Y. Jin, M. Olhofer and B. Sendhoff. Dynamic Weighted Aggregation for Evolutionary Multi-Objective Optimization: Why Does It Work and How? In: Proceedings of the 3rd Annual Conference on Genetic and Evolutionary Computation (GECCO'01) (San Francisco, California, 2001); pp. 1042–1049. ↩1 ↩2 ↩3 ↩4
- [16]
- I. Y. Kim and O. L. de Weck. Adaptive weighted-sum method for bi-objective optimization: Pareto front generation. Structural and Multidisciplinary Optimization 29, 149–158 (2005). ↩1 ↩2
- [17]
- J. Lis and A. E. Eiben. A multi-sexual genetic algorithm for multiobjective optimization. In: Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97) (1997); pp. 59–64. ↩1 ↩2
- [18]
- [19]
- E. Zitzler, K. Deb and L. Thiele. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Evolutionary Computation 8, 173–195 (2000). ↩1 ↩2 ↩3 ↩4 ↩5 ↩6
- [20]
- M. Laumanns, L. Thiele, K. Deb and E. Zitzler. Combining Convergence and Diversity in Evolutionary Multiobjective Optimization. Evolutionary Computation 10, 263–282 (2002). ↩1 ↩2
- [21]
- J. J. Moré, B. S. Garbow and K. E. Hillstrom. Testing Unconstrained Optimization Software. ACM Trans. Math. Softw. 7, 17–41 (1981). ↩1 ↩2 ↩3 ↩4 ↩5 ↩6 ↩7
- [22]
- [23]
- J. Mao, K. Hirasawa, J. Hu and J. Murata. Genetic symbiosis algorithm for multiobjective optimization problem. In: Proceedings 9th IEEE International Workshop on Robot and Human Interactive Communication. IEEE RO-MAN 2000 (Cat. No.00TH8499) (2000); pp. 137–142. ↩1 ↩2
- [24]
- [25]
- E. Miglierina, E. Molho and M. C. Recchioni. Box-constrained multi-objective optimization: A gradient-like method without ``a priori'' scalarization. European Journal of Operational Research 188, 662–682 (2008). ↩1 ↩2
- [26]
- M. Preuss, B. Naujoks and G. Rudolph. Pareto Set and EMOA Behavior for Simple Multimodal Multiobjective Functions. In: Parallel Problem Solving from Nature - PPSN IX, edited by T. P. Runarsson, H.-G. Beyer, E. Burke, J. J. Merelo-Guervós, L. D. Whitley and X. Yao (Springer Berlin Heidelberg, Berlin, Heidelberg, 2006); pp. 513–522. ↩1 ↩2
- [27]
- D. Quagliarella and A. Vicini. Sub-population policies for a parallel multiobjective genetic algorithm with applications to wing design. In: SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218), Vol. 4 (1998); p. 3142–3147 vol.4. ↩1 ↩2
- [28]
- W. Stadler and J. Dauer. Multicriteria Optimization in Engineering: A Tutorial and Survey. In: Structural Optimization: Status and Promise, edited by M. P. Kamat (American Institute of Aeronautics and Astronautics, Washington, DC, 1992); pp. 209–249. ↩1 ↩2 ↩3
- [29]
- K. Socha and M. Kisiel-Dorohinicki. Agent-based evolutionary multiobjective optimisation. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), Vol. 1 (2002); p. 109–114 vol.1. ↩1 ↩2 ↩3
- [30]
- O. Schütze, M. Laumanns, C. A. Coello Coello, M. Dellnitz and E.-G. Talbi. Convergence of stochastic search algorithms to finite size pareto set approximations. Journal of Global Optimization 41, 559–577 (2008). ↩1 ↩2
- [31]
- M. Sefrioui and J. Perlaux. Nash genetic algorithms: examples and applications. In: Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512), Vol. 1 (2000); p. 509–516 vol.1. ↩1 ↩2
- [32]
- M.-B. Shim, M.-W. Suh, T. Furukawa, G. Yagawa and S. Yoshimura. Pareto-based continuous evolutionary algorithms for multiobjective optimization. Engineering Computations 19, 22–48 (2002). ↩1 ↩2
- [33]
- K. C. Tan, E. F. Khor, T. H. Lee and Y. J. Yang. A Tabu-Based Exploratory Evolutionary Algorithm for Multiobjective Optimization. Artificial Intelligence Review 19, 231–260 (2003). ↩1 ↩2
- [34]
- [35]
- [36]
- D. A. Van Veldhuizen. Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. Ph.D. dissertation, Air Force Institute of Technology (Wright-Patterson AFB, OH, 06 1999). ↩1 ↩2
- [37]
- E. Zitzler, M. Laumanns and L. Thiele. SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Technical Report TIK-Report 103 (Computer Engineering and Networks Laboratory (TIK), ETH Zurich, 05 2001). ↩1 ↩2 ↩3 ↩4 ↩5 ↩6
- [38]
- C. M. Fonseca and P. J. Fleming. Multiobjective genetic algorithms made easy: selection, sharing and mating restriction. In: First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA) (IEE, Sheffield, UK, 1995); pp. 45–52. ↩1
- [39]
- C. Poloni, G. Mosetti and S. Contessi. Multi objective optimization by GAs: application to system and component design. In: Computational Methods in Applied Sciences '96: Invited Lectures and Special Technological Sessions of the Third ECCOMAS Computational Fluid Dynamics Conference and the Second ECCOMAS Conference on Numerical Methods in Engineering, edited by J.-A. Désidéri, C. Hirsch, P. Le Tallec, M. Pandolfi and others (John Wiley & Sons, Chichester, 1996); pp. 258–264. ↩1
- [40]
- R. Viennet, C. Fonteix and I. Marc. Multicriteria optimization using a genetic algorithm for determining a Pareto set. International Journal of Systems Science 27, 255–260 (1996). ↩1 ↩2
- [41]
- [42]
- J. D. Schaffer. Multiple objective optimization with vector evaluated genetic algorithms. In: Proceedings of an International Conference on Genetic Algorithms and Their Applications, edited by J. J. Grefenstette (Pittsburgh, PA, 1985); pp. 93–100. Sponsored by Texas Instruments and the U.S. Navy Center for Applied Research in Artificial Intelligence (NCARAI). ↩1
- [43]
- M. Laumanns, G. Rudolph and H.-P. Schwefel. Mutation control and convergence in evolutionary multi-objective optimization. In: Proceedings of the 7th International Mendel Conference on Soft Computing (MENDEL 2001) (Brno, Czech Republic, 06 2001). ↩1