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MP (Mathematical Programming)

  • Diouane, Y., Gratton, S. and Vicente, L.N., 2015. Globally convergent evolution strategies. Mathematical Programming, 152(1), pp.467-490. [ www ] ( ES | Continuous Optimization )
  • Dekkers, A. and Aarts, E., 1991. Global optimization and simulated annealing. Mathematical Programming, 50(1), pp.367-393. [ www ] ( SA )

2018

Cozad, A., and Sahinidis, N. V. (2018). A global MINLP approach to symbolic regression. Mathematical Programming, 170(1), 97–119. [www] (GA)

2016

Stich, S. U., Müller, C. L., and Gärtner, B. (2016). Variable metric random pursuit. Mathematical Programming, 156(1), 549–579. [www] (CMA-ES)

2007

Grosso, A., Locatelli, M., and Schoen, F. (2007). A population-based approach for hard global optimization problems based on dissimilarity measures. Mathematical Programming, 110(2), 373–404. [www]

2004

Liuzzi, G., Lucidi, S., Piccialli, V., and Sotgiu, A. (2004). A magnetic resonance device designed via global optimization techniques. Mathematical Programming, 101(2), 339–364. [www] (SA)

2003

Christofides, S., Christofides, A., and Christofides, N. (2003). The design of corporate tax structures. Mathematical Programming, 98(1), 493–510. [www] (GA)

Xie, D., Singh, S. B., Fluder, E. M., and Schlick, T. (2003). Principal component analysis combined with truncated-newton minimization for dimensionality reduction of chemical databases. Mathematical Programming, 95(1), 161–185. [www] (SA)

2001

Wood, G. R., Zabinsky, Z. B., and Kristinsdottir, B. P. (2001). Hesitant adaptive search: The distribution of the number of iterations to convergence. Mathematical Programming, 89(3), 479–486. [www] (SA)

1998

Bulger, D. W., and Wood, G. R. (1998). Hesitant adaptive search for global optimisation. Mathematical Programming, 81(1), 89–102. [www] (SA)

1997

Yackel, J., Meyer, R. R., and Christou, I. (1997). Minimum-perimeter domain assignment. Mathematical Programming, 78(2), 283–303. [www] (GA)

  • Cartis, C. and Roberts, L., 2023. Scalable subspace methods for derivative-free nonlinear least-squares optimization. Mathematical Programming, 199(1-2), pp.461-524.
  • Vicente, L.N. and Custódio, A.L., 2012. Analysis of direct searches for discontinuous functions. Mathematical Programming, 133, pp.299-325.
  • Byrd, R.H., Dert, C.L., Rinnooy Kan, A.H. and Schnabel, R.B., 1990. Concurrent stochastic methods for global optimization. Mathematical Programming, 46(1-3), pp.1-29.
  • Rinnooy Kan, A.H.G. and Timmer, G.T., 1987. Stochastic global optimization methods part II: Multi level methods. Mathematical Programming, 39, pp.57-78.
  • Rinnooy Kan, A.H.G. and Timmer, G.T., 1987. Stochastic global optimization methods part I: Clustering methods. Mathematical Programming, 39, pp.27-56.
  • Betrò, B. and Schoen, F., 1987. Sequential stopping rules for the multistart algorithm in global optimisation. Mathematical Programming, 38(3), pp.271-286.
  • Boender, C.G.E. and Rinnooy Kan, A.H.G., 1987. Bayesian stopping rules for multistart global optimization methods. Mathematical Programming, 37, pp.59-80.
  • Boender, C.G.E., Rinnooy Kan, A.H.G., Timmer, G.T. and Stougie, L., 1982. A stochastic method for global optimization. Mathematical Programming, 22, pp.125-140.
  • Devroye, L.P., 1978. Progressive global random search of continuous functions. Mathematical Programming, 15(1), pp.330-342.
  • Schrack, G. and Choit, M., 1976. Optimized relative step size random searches. Mathematical Programming, 10(1), pp.230-244.