By F. H. Clarke, R. J. Stern (auth.), Nicolas Hadjisavvas, Panos M. Pardalos (eds.)
There has been a lot fresh development in worldwide optimization algo rithms for nonconvex non-stop and discrete difficulties from either a theoretical and a realistic standpoint. Convex research performs a enjoyable damental position within the research and improvement of world optimization algorithms. this is often due primarily to the truth that almost all noncon vex optimization difficulties could be defined utilizing changes of convex services and adjustments of convex units. A convention on Convex research and international Optimization was once held in the course of June five -9, 2000 at Pythagorion, Samos, Greece. The convention was once honoring the reminiscence of C. Caratheodory (1873-1950) and was once en dorsed through the Mathematical Programming Society (MPS) and through the Society for business and utilized arithmetic (SIAM) job workforce in Optimization. The convention used to be subsidized via the ecu Union (through the EPEAEK program), the dept of arithmetic of the Aegean college and the guts for utilized Optimization of the collage of Florida, by means of the final Secretariat of study and Tech nology of Greece, through the Ministry of schooling of Greece, and several other neighborhood Greek govt businesses and corporations. This quantity includes a selective choice of refereed papers according to invited and contribut ing talks offered at this convention. the 2 topics of convexity and worldwide optimization pervade this booklet. The convention supplied a discussion board for researchers engaged on varied points of convexity and international opti mization to give their fresh discoveries, and to engage with humans engaged on complementary points of mathematical programming.
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Additional info for Advances in Convex Analysis and Global Optimization: Honoring the Memory of C. Caratheodory (1873–1950)
These observations, and the importance of the protein folding and peptide docking problems, have propelled the introduction of new global search strategies specifically designed for these problems. In the sequel, we first outline the basics of the deterministic global optimization approach, aBB, which has been used extensively to study the protein structure prediction. This is followed by a comprehensive study of ab-initio modeling for structure prediction of single chain polypeptides. An extensive comparison of energy modeling, including solvation, entropic effects and free energy calculations, is provided for the oligopeptides.
00-01-00454) 11 N. M. ), Advances in Convex Analysis and Global Optimization, 11-30. © 2001 Kluwer Academic Publishers. , to identify as many points as possible or to minimize the number of unidentified points). In the paper the identification problems are treated as optimization problems. More sophisticated models are described by nonsmooth optimization problems. An algorithm is suggested allowing to construct a sequence of linear criterion functions which can be used for the identification of the points of the sets.
1), namely, stochastic and deterministic ap- 33 34 ADVANCES IN CONVEX ANALYSIS AND GLOBAL OPTIMIZATION proaches. Stochastic methods, such as those based on genetic algorithms  and simulated annealing , can be used to treat unconstrained nonconvex problems. However, the stochastic nature of the search strategy invalidates any claims regarding global optimality since it is impossible to obtain valid bounds on the solution of the problem. The addition of nonconvex constraints further complicates these solution schemes.