Abstract
Global optimization is a highly active research field in the intersection of continuous and combinatorial optimization (a basic web search delivers overa million hits for this phrase and for its British cousin, Global Optimisation).A variety of methods have been devised to deal with this problem class, which – borrowing biological taxonomy terminology in a very superficial way – may be divided roughly into the two domains of exact/rigorous methods and heuristics, the difference between them probably being that you can prove less theorems in the latter domain. Breaking the domain of exact methods into two phyla of deterministic methods and stochastic methods, we may have the following further taxonomy of the deterministic phylum:
implicit enumeration methods: branch & bound
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References
Anstreicher, K., and S. Burer, D.C. Versus Copositive Bounds for Standard QP, J. Global Optimiz., 33, 2005, 299–312.
Bomze, I.M., Remarks on the recursive structure of copositivity, J. Inf. & Optimiz. Sciences, 8, 1987, 243–260.
Bomze, I.M., Copositivity conditions for global optimality in indefinite quadratic programming problems, Czechoslovak J. Operations Research 1, 1992, 7–19.
Bomze, I.M., Block pivoting and shortcut strategies for detecting copositivity, Linear Alg. Appl. 248, 1996, 161–184.
Bomze, I.M., Evolution towards the maximum clique, J. Global Optimiz., 10, 1997, 143–164.
Bomze, I.M., On standard quadratic optimization problems, J. Global Optimiz., 13, 1998, 369–387.
Bomze, I.M., Linear-time detection of copositivity for tridiagonal matrices and extension to block-tridiagonality, SIAM J. Matrix Anal. Appl. 21, 2000, 840–848.
Bomze, I.M., Branch-and-bound approaches to standard quadratic optimization problems, J. Global Optimiz., 22, 2002, 17–37.
Bomze, I.M., Portfolio selection via replicator dynamics and projection of indefinite estimated covariances, Dynamics of Continuous, Discrete and Impulsive Systems B 12, 2005, 527–564.
Bomze, I.M., Perron-Frobenius property of copositive matrices, and a block copositivity criterion, Linear Algebra and its applications, 429, 2008, 68–71.
Bomze, I.M., and G. Danninger, A global optimization algorithm for concave quadratic problems, SIAM J. Optimiz., 3, 1993, 836–842.
Bomze, I.M., M. Dür, E. de Klerk, A. Quist, C. Roos, and T. Terlaky, On copositive programming and standard quadratic optimization problems, J. Global Optimiz., 18, 2000, 301–320.
Bomze, I.M., and E. de Klerk, Solving standard quadratic optimization problems via linear,semidefiniteandcopositiveprogramming, J. GlobalOptimiz., 24, 2002, 163–185.
Bomze, I.M., F. Frommlet, and M. Rubey, Improved SDP bounds for minimizing quadratic functions over the ℓ 1 -ball, Optimiz. Letters, 1, 2007, 49–59.
Bomze, I.M., M. Locatelli, and F. Tardella, Efficient and cheap bounds for (standard) quadratic optimization, Technical Report dis tr 2005/10, 2005, Dipartimento di Informatica e Sistemistica “Antonio Ruberti”, Universitá degli Studi di Roma “La Sapienza”, available at www.optimization-online.org/DB_HTML/2005/07/1176.html, last accessed 12 May 2006.
Bomze, I.M., M. Locatelli, and F. Tardella, New and old bounds for standard quadratic optimization: dominance, equivalence and incomparability, Math. Programming. 115, 2008, 31–64.
Bomze, I.M., and L. Palagi, Quartic formulation of standard quadratic optimization problems, J. Global Optimiz., 32, 2005, 181–205.
Bomze, I.M., and V. Stix, Genetical engineering via negative fitness: evolutionary dynamics for global optimization, Annals of O.R. 89, 1999, 279–318.
Bonnans, J. F. and C. Pola, A trust region interior point algorithm for linearly constrained optimization, SIAM J. Optim., 7, 1997, 717–731.
Borwein, J.M., Necessary and sufficient conditions for quadratic minimality, Numer. Funct. Anal. and Optimiz., 5, 1982, 127–140.
Boyd, S., and L. Vandenberghe, Convex Optimization, Cambridge Univ. Press, Cambridge, UK., 2004.
Burer, S., On the copositive representation of binary and continuous nonconvex quadratic programs, preprint, 2006, Univ. of Iowa, available at http://www.optimization-online.org/DB_FILE/2006/10/1501.pdf, last accessed Jan. 08, to appear in: Math Programming (2009).
Contesse B., L., Une caractérisation complète des minima locaux en programmation quadratique, Numer. Math. 34, 1980, 315–332.
Cottle, R.W., J.-S. Pang, and R.E. Stone, The Linear Complementarity Problem. Academic Press, New York., 1992.
Danninger, G., A recursive algorithm for determining (strict) copositivity of a symmetric matrix, in: U. Rieder et al. (eds.), Methods of Operations Research 62, 1990,45–52. Hain, Meisenheim.
Danninger, G., Role of copositivity in optimality criteria for nonconvex optimization problems, J. Optimiz. Theo. Appl. 75, 1992,535–558.
Danninger, G., and I.M. Bomze, Using copositivity for global optimality criteria in concave quadratic programming problems, Math. Programming 62, 1993, 575–580.
de Klerk, E., The complexity of optimizing over a simplex, hypercube or sphere: a short survey,, Central European J. OR 16, 2008,111–128.
de Klerk, E., and D.V. Pasechnik, Approximation of the stability number of a graph via copositive programming, SIAM J. Optimiz. 12, 2002, 875–892.
Diananda, P.H., On non-negative forms in real variables some or all of which are non-negative, Proc. Cambridge Philos. Soc. 58, 1962, 17–25.
Dür, M., Duality in Global Optimization – Optimality conditions and algorithmical aspects. Shaker, Aachen, 1999.
Dür, M., A parametric characterization of local optimality, Math. Methods Oper. Res. 57, 2003, 101–109.
Dür, M., and G. Still, Interior points of the completely positive cone, Electronic J. Linear Algebra 17, 2008,48–53.
Fisher, R.A., The Genetical Theory of Natural Selection. Clarendon Press, Oxford, 1930.
Gonzaga, C.C. and L.A. Carlos, A primal affine scaling algorithm for linearly constrained convex programs, Tech. Report ES-238/90, COPPE Federal Univ.Rio de Janeiro, 1990.
Hadeler, K.P. On copositive matrices, Linear Alg. Appl. 49, 1983, 79–89.
Hall, M. Jr., and M. Newman Copositive and Completely Positive Quadratic Forms, Proc. Cambridge Philos. Soc. 59, 1963, 329–339.
Hiriart-Urruty, J.-B., From Convex Optimization to Nonconvex Optimization, Part I: Necessary and sufficient conditions for Global Optimality, in: F.H. Clarke et al. (eds.), Nonsmooth Optimization and Related Topics, 1989, 219–239, Plenum Press, New York.
Hiriart-Urruty, J.-B., and C. Lemaréchal, Testing necessary and sufficient conditions for global optimality in the problem of maximizing a convex quadratic function over a convex polyhedron, Preliminary report, University Paul Sabatier, Toulouse, 1990.
Hiriart-Urruty, J.-B., and C. Lemaréchal, Convex Analysis and Minimization Algorithms II. Grundlehren der Mathematik 306, Springer, Berlin, 1996.
Hofbauer, J. and Sigmund, K., Evolutionary Games and Population Dynamics, Cambridge University Press, Cambridge, UK, 1998.
Horst, R., and H. Tuy, Global optimization – deterministic approaches. Springer, Berlin, 1991.
Ikramov, Kh.D., Linear-time algorithm for verifying the copositivity of an acyclic matrix, Comput. Math. Math. Phys. 42, 2002, 1701–1703.
Johnson, C.R., and R. Reams, Spectral theory of copositive matrices, Linear Algebra and its Applications 395, 2005, 275–281.
Lasserre, J.B., Global optimization with polynomials and the problem of moments, SIAM Journal on Optimization 11, 2001, 796–817.
Lasserre, J.B., An explicit exact SDP relaxation for nonlinear 0-1 programming, In: K. Aardal and A.H.M. Gerards, eds., Lecture Notes in Computer Science 2081, 2001, 293–303.
Lyubich, Yu., G. D. Maistrowskii, and Yu. G. Ol’khovskii, Selection-induced convergence to equilibrium in a single-locus autosomal population, Problems of Information Transmission, 16, 1980, 66–75.
Majthay, A., Optimality conditions for quadratic programming, Math. Programming, 1, 1971, 359–365.
Monteiro, R. D. C. and Y. Wang, Y., Trust region affine scaling algorithms for linearly constrained convex and concave programs, Math. Programming. 80, 1998, 283–313.
Moran, P. A. P., The Statistical Processey, Oxford, Clarendon Press, 1962.
Motzkin, T.S., and E.G. Straus, Maxima for graphs and a new proof of a theorem of Turán, Canadian J. Math. 17, 1965,533–540.
Murty, K.G., and S.N. Kabadi, Some NP-complete problems in quadratic and linear programming, Math. Programming 39, 1987, 117–129.
Nesterov, Y.E., Global Quadratic Optimization on the Sets with Simplex Structure, Discussion paper 9915, CORE, Catholic University of Louvain, Belgium, 1999.
Nesterov, Y.E., and A. Nemirovski, Interior Point Polynomial Algorithms in Convex Programming. SIAM Publications. SIAM, Philadelphia, USA, 1994.
Ozdaglar, A., and P. Tseng, Existence of Global Minima for Constrained Optimization, J. Optimiz. Theo. Appl. 128, 2006, 523–546.
Parrilo, P.A., Structured Semidefinite Programs and Semi-algebraic Geometry Methods in Robustness and Optimization, PhD thesis, California Institute of Technology, Pasadena, USA, 2000. Available at: http://www.cds.caltech.edu/ \(\tilde{}\) pablo/.
Parrilo, P.A., Semidefinite programming relaxations for semi-algebraic problems, Math. Programming 696B, 2003, 293–320.
Pavan, M., and M. Pelillo, Dominant sets and pairwise clustering, IEEE Trans. on Pattern Analysis and Machine Intelligence, 29, 2007, 167–172.
Pelillo, M., Matching free trees, maximal cliques, and monotone game dynamics, IEEE Trans. Pattern Anal. Machine Intell., 24, 2002, 1535–1541.
Peña J., J. Vera, and L. Zuluaga, Computing the stability number of a graph via linear and semidefinite programming, SIAM J. Optimiz., 18, 2007, 87–105.
Poljak, S., and Z. Tuza, Maximum cuts and largest bipartite subgraphs, in: W. Cook, L. Lovasz, and P. Seymour (eds.), Combinatorial Optimization, 1995, pp. 181–244, American Mathematical Society, Baltimore.
Scozzari, A., and F. Tardella, A clique algorithm for standard quadratic programming, 2008, to appear in Discrete Applied Mathematics.
Sun, J., A convergence proof for an affine-scaling algorithm for convex quadratic programming without nondegeneracy assumptions, Math. Programming 60, 1993, 69–79.
Tseng, P., Convergence properties of Dikin’s affine scaling algorithm for nonconvex quadratic minimization, J. Global Optim., 30, 2004, 285–300.
Tseng, P., A scaled projected reduced-gradient method for linearly constrained smooth optimization, preprint, 2007, Univ. of Washington.
Tseng, P., I.M. Bomze, W. Schachinger, A first-order interior-point method for Linearly Constrained Smooth Optimization, preprint, 2007, to appear in: Math Programming (2009).
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Bomze, I.M. (2010). Global Optimization: A Quadratic Programming Perspective. In: Di Pillo, G., Schoen, F. (eds) Nonlinear Optimization. Lecture Notes in Mathematics(), vol 1989. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11339-0_1
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