Abstract
In this paper we show that optimal design of experiments, a specific topic in statistics, constitutes a challenging application field for global optimization. This paper shows how various structures in optimal design of experiments problems determine the structure of corresponding challenging global optimization problems. Three different kinds of experimental designs are discussed: discrete designs, exact designs and replicationfree designs. Finding optimal designs for these three concepts involves different optimization problems.
Similar content being viewed by others
References
Atkinson, A.C. (1996), The usefulness of optimum experimental designs, Journal of the Royal Statistical Society B 58(1): 59-76.
Atkinson, A.C. and Donev, A.N. (1992), Optimum experimental designs. Oxford University Press, Oxford.
Boer, E.P.J., Rasch, D.A.M.K. and Hendrix, E.M.T. (2000), Locally optimal designs in non-linear regression: A case study of the Michaelis-Menten function, in Balakrishnan, N., Ermakov, S.M. and Melas, V.B. (eds.), Advances in Stochastic Simulation Methods, Birkhauser, Boston.
Ermakov, S.M. and Zhiglijavsky, A.A. (1987), Matematitscheskaja teorija optimalnich experimentov. Nauka, Moskva.
Fedorov, V.V. (1972), Theory of optimal experiments. Academic Press, New York.
Fedorov, V.V. (1989), Optimal design with bounded density: Optimization algorithms of the exchange type, Journal of Statistical Planning and Inference 22: 1-13.
Gaffke, N. and Mathar, R. (1992), On a class of algorithms from experimental design theory, Optimization 24: 91-126.
Gaffke, N. and Heiligers, B. (1995), Algorithms for optimal design with application to multiple polynomial regression, Metrika 42: 173-190.
Jones, B. and Wang, J. (1999), Constructing optimal designs for fitting pharmacokinetic models, Computational Statistics 9: 209-218.
Kiefer, J.C. and Wolfowitz, J. (1960), The equivalence of two extremum problems, Canadian Journal of Mathematics 12: 363-366.
Ko, C., Lee, J. and Queyranne, M. (1995), An exact algorithm for maximum entropy sampling, Operations Research 43(4): 684-691.
Müller, W.G. (1998), Collecting spatial Data–Optimum design of experiments for random fields. Physica-Verlag, Heidelberg.
Müller, W.G. and Pázmann, A. (1998), Design measures and approximate information matrices for experiments without replications, Journal of Statistical Planning and Inference 71: 349-362.
Pukelsheim, F. (1993), Optimal design of experiments. Wiley, New York.
Pukelsheim, F. and Rieder, S. (1992), Efficient rounding of approximate designs, Biometrika 79(4): 763-770.
Rasch, D.A.M.K. (1990), Optimum experimental design in nonlinear regression, Commun. Statist.-Theory Meth. 19(12): 4789-4806.
Rasch, D.A.M.K., Hendrix, E.M.T. and Boer E.P.J. (1997), Replication-free optimal design in regresion analysis, Computational Statistics 12: 19-52.
Silvey, S.D. (1980), Optimal design. Chapman and Hall, London.
Vila, J.P. (1991), Local optimality of replications from a minimal D-optimal design in regression: A sufficient and quasi-necessary condition, Journal of Statistical Planning and Inference 29: 261-277.
Welch, W.J. (1982), Branch-and-Bound search for experimental designs based on D optimality and other criteria, Technometrics 24(1): 41-48.
White, L.V. (1973), An extension to the general equivalence theorem for nonlinear models, Biometrika 60: 345-348.
Zhigljavsky, A.A. (1991), Theory of Global Random Search. Kluwer Academic Publishers, Dordrecht.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Boer, E., Hendrix, E. Global Optimization Problems in Optimal Design of Experiments in Regression Models. Journal of Global Optimization 18, 385–398 (2000). https://doi.org/10.1023/A:1026552318150
Issue Date:
DOI: https://doi.org/10.1023/A:1026552318150