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54. D. Agnew, Improved minimax optimization for circuit design. IEEE Trans. Circuits Syst.
28(8), 791–803 (1981)
55. J. Shinn-Hwa Wang, W. Wei-Ming Dai, Transformation of min-max optimization to leastsquare estimation and application to interconnect design optimization, in Proceedings of
ICCD’95 International Conference on Computer Design. VLSI in Computers and Processors
(IEEE Computer Society Press, Washington, 1995), pp. 664–670
56. B. Lu, Y. Cao, M. Yuan, J. Zhou, Reference variable methods of solving minmax optimization
problems. J. Global Optim. 42(1), 1–21 (2008)
57. M. Sainz, P. Herrero, J. Armengol, J. Veh, Continuous minimax optimization using modal
intervals. J. Math. Anal. Appl 339, 18–30 (2008)
58. Y. Feng, L. Hongwei, Z. Shuisheng, L. Sanyang, A smoothing trust-region Newton-CG
method for minimax problem. Appl. Math. Comput. 199(2), 581–589 (2008)
59. P. Parpas, B. Rustem, An algorithm for the global optimization of a class of continuous
minimax problems. J. Optim. Theory Appl. 141, 46–173 (2009). https://doi.org/10.1007/
s10957-008-9473-4
60. H. Aissi, C. Bazgan, D. Vanderpooten, Min-max and min-max regret versions of combinatorial optimization problems: a survey. Eur. J. Oper. Res. 197, 427–438 (2009)
61. T.M. Cavalier, W.A. Conner, E. del Castillo, S.I. Brown, A heuristic algorithm for minimax
sensor location in the plane. Eur. J. Oper. Res. 183(1), 42–55 (2007)
62. D. Ahr, G. Reinelt, A tabu search algorithm for the min-max k-Chinese postman problem.
Comput. Oper. Res. 33(12), 3403–3422 (2006)
63. A.M. Cramer, S.D. Sudhoff, E.L. Zivi, Evolutionary algorithms for minimax problems in
robust design. IEEE Trans. Evol. Comput. 13(2), 444–453 (2009)
64. R.I. Lung, D. Dumitrescu, A new evolutionary approach to minimax problems, in IEEE
Congress on Evolutionary Computation (CEC), 5–8 June 2011, New Orleans (2011), pp.
1902–1905. https://doi.org/10.1109/CEC.2011.5949847
65. A. Zhou, Q. Zhang, A surrogate-assisted evolutionary algorithm for minimax optimization,
in IEEE Conference on Evolutionary Computation (CEC) (2010)
66. E.C. Laskari, K.E. Parsopoulos, M.N. Vrahatis, Particle swarm optimization for minimax
problems, in Proceedings of the 2002 Congress on Evolutionary Computation (IEEE Press,
New York, 2002), pp. 1582–1587
67. W. Conner, Comparison of evolutionary algorithms on the minimax sensor location problem.
The Pennsylvania State University, 310.
68. A.M. Cramer, S.D. Sudhoff, E.L. Zivi, Evolutionary algorithms for minimax problems in
robust design. IEEE Trans. Evol. Comput. 13, 444–453 (2009). https://doi.org/10.1109/
TEVC.2008.2004422
69. D. Agnew, Improved minimax optimization for circuit design. IEEE Trans. Circuits Syst.
28(8), 791–803 (1981)
70. A.V. Sebald, J. Schlenzig, Minimax design of neural net controllers for highly uncertain
plants. IEEE Trans. Neural Netw. 5(1), 73–82 (1994)
71. H.J.C. Barbosa, A coevolutionary genetic algorithm for a game approach to structural
optimization, in Proceedings of the 7-th International Conference on Genetic Algorithms
(1997), pp. 545–552
72. H.J.C. Barbosa, A coevolutionary genetic algorithm for constrained optimization, in Proceedings of 1999 Congress on Evolutionary Computation, ed. by P. Angeline et. al. (1997), pp.
1605–1611
73. J.W. Herrmann, A genetic algorithm for minimax optimization problems, in Proceedings of
1999 Congress on Evolutionary Computation, ed. by P. Angeline et. al. (1997), pp. 1099–1103
74. T.M. Jensen, A new look at solving minimax problems with coevolutionary genetic
algorithms, in Metaheuristics: Computer Decision-Making. Applied Optimization, vol. 86
(Springer, Boston, 2003), pp 369–384
75. Y.S. Ong, P.B. Nair, A.J. Keane, K.W. Wong, Surrogate-assisted evolutionary optimization
frameworks for high-fidelity engineering design problems, in Knowledge Incorporation in
Evolutionary Computation (Springer, Berlin, 2004), pp. 307–332
G. Filippi and M. Vasile
54. D. Agnew, Improved minimax optimization for circuit design. IEEE Trans. Circuits Syst.
28(8), 791–803 (1981)
55. J. Shinn-Hwa Wang, W. Wei-Ming Dai, Transformation of min-max optimization to leastsquare estimation and application to interconnect design optimization, in Proceedings of
ICCD’95 International Conference on Computer Design. VLSI in Computers and Processors
(IEEE Computer Society Press, Washington, 1995), pp. 664–670
56. B. Lu, Y. Cao, M. Yuan, J. Zhou, Reference variable methods of solving minmax optimization
problems. J. Global Optim. 42(1), 1–21 (2008)
57. M. Sainz, P. Herrero, J. Armengol, J. Veh, Continuous minimax optimization using modal
intervals. J. Math. Anal. Appl 339, 18–30 (2008)
58. Y. Feng, L. Hongwei, Z. Shuisheng, L. Sanyang, A smoothing trust-region Newton-CG
method for minimax problem. Appl. Math. Comput. 199(2), 581–589 (2008)
59. P. Parpas, B. Rustem, An algorithm for the global optimization of a class of continuous
minimax problems. J. Optim. Theory Appl. 141, 46–173 (2009). https://doi.org/10.1007/
s10957-008-9473-4
60. H. Aissi, C. Bazgan, D. Vanderpooten, Min-max and min-max regret versions of combinatorial optimization problems: a survey. Eur. J. Oper. Res. 197, 427–438 (2009)
61. T.M. Cavalier, W.A. Conner, E. del Castillo, S.I. Brown, A heuristic algorithm for minimax
sensor location in the plane. Eur. J. Oper. Res. 183(1), 42–55 (2007)
62. D. Ahr, G. Reinelt, A tabu search algorithm for the min-max k-Chinese postman problem.
Comput. Oper. Res. 33(12), 3403–3422 (2006)
63. A.M. Cramer, S.D. Sudhoff, E.L. Zivi, Evolutionary algorithms for minimax problems in
robust design. IEEE Trans. Evol. Comput. 13(2), 444–453 (2009)
64. R.I. Lung, D. Dumitrescu, A new evolutionary approach to minimax problems, in IEEE
Congress on Evolutionary Computation (CEC), 5–8 June 2011, New Orleans (2011), pp.
1902–1905. https://doi.org/10.1109/CEC.2011.5949847
65. A. Zhou, Q. Zhang, A surrogate-assisted evolutionary algorithm for minimax optimization,
in IEEE Conference on Evolutionary Computation (CEC) (2010)
66. E.C. Laskari, K.E. Parsopoulos, M.N. Vrahatis, Particle swarm optimization for minimax
problems, in Proceedings of the 2002 Congress on Evolutionary Computation (IEEE Press,
New York, 2002), pp. 1582–1587
67. W. Conner, Comparison of evolutionary algorithms on the minimax sensor location problem.
The Pennsylvania State University, 310.
68. A.M. Cramer, S.D. Sudhoff, E.L. Zivi, Evolutionary algorithms for minimax problems in
robust design. IEEE Trans. Evol. Comput. 13, 444–453 (2009). https://doi.org/10.1109/
TEVC.2008.2004422
69. D. Agnew, Improved minimax optimization for circuit design. IEEE Trans. Circuits Syst.
28(8), 791–803 (1981)
70. A.V. Sebald, J. Schlenzig, Minimax design of neural net controllers for highly uncertain
plants. IEEE Trans. Neural Netw. 5(1), 73–82 (1994)
71. H.J.C. Barbosa, A coevolutionary genetic algorithm for a game approach to structural
optimization, in Proceedings of the 7-th International Conference on Genetic Algorithms
(1997), pp. 545–552
72. H.J.C. Barbosa, A coevolutionary genetic algorithm for constrained optimization, in Proceedings of 1999 Congress on Evolutionary Computation, ed. by P. Angeline et. al. (1997), pp.
1605–1611
73. J.W. Herrmann, A genetic algorithm for minimax optimization problems, in Proceedings of
1999 Congress on Evolutionary Computation, ed. by P. Angeline et. al. (1997), pp. 1099–1103
74. T.M. Jensen, A new look at solving minimax problems with coevolutionary genetic
algorithms, in Metaheuristics: Computer Decision-Making. Applied Optimization, vol. 86
(Springer, Boston, 2003), pp 369–384
75. Y.S. Ong, P.B. Nair, A.J. Keane, K.W. Wong, Surrogate-assisted evolutionary optimization
frameworks for high-fidelity engineering design problems, in Knowledge Incorporation in
Evolutionary Computation (Springer, Berlin, 2004), pp. 307–332