Int. J. Mol. Sci. 3, 30 (2002)]; Phys. Rev. E 66, 046704 (2002)]] a method for global optimization, according to which the global minimum of a potential V(f) can be found, if a potential V(i) (with a known global minimum) is transformed adiabatically in time to V(f) , with the use of a switching function of time g (t) , which interpolates between 0 and 1, and lies in the [0,1] interval. In the ...

{Global optimization approaches are proposed for addressing both the protein folding and peptide docking problems. In the protein folding problem, the ultimate goal involves predicting the native protein conformation. A common approach, based on the thermodynamic hypothesis, assumes that this conformation corresponds to the structure exhibiting the global minimum free energy. However, molecular...

OBJECTIVE To compare the reliability of quantitative measurement of minimum hip joint space with a qualitative global assessment of radiological features for estimating the prevalence of primary osteoarthritis (OA) of the hip in colon radiographs. METHODS All colon radiographs from patients aged 35 or older, taken at three different radiographic departments in Iceland during the years 1990-96...

An H2 control performance criterion dependent on a controller parameter vector is analyzed from the point of view of evaluating the domain of attraction of its global minimum when a gradient-based algorithm is used in tuning the parameters. The objective of this analysis is twofold: (i) examine how some design parameters of the criterion can be used to enlarge the domain of attraction; (ii) exa...

most scientists believe that the phenomenon of global warming occurred, however, in the case of the occurrence of this phenomenon by some environmental scientists have raised doubts. they are questioning global warming by arguing that the temperature recorded at the weather stations cannot be representative of the occurrence of the temperature rise. because with the passage of time and the incr...

The objective of global optimization is to find the globally best solution of a model. Nonlinear models are ubiquitous in many applications and their solution often requires a global search approach; i.e. for a function f from a set A ⊂ R to the real numbers, an element x0 ∈ A is sought-after, such that ∀x ∈ A : f(x0) ≤ f(x). Depending on the field of application, the question whether a found s...

In this paper a branch-and-bound algorithm is proposed for finding a global minimum to a Mathematical Programming Problem with Complementarity (or Equilibrium) Constraints (MPECs), which incorporates disjunctive cuts for computing lower bounds and employs a Complementarity Active-Set Algorithm for computing upper bounds. Computational results for solving MPECs associated with Bilivel Problems, ...

A global optimization method is presented for predicting the minimum energy structure of small protein-like molecules. This method begins by collecting a large number of molecular conformations, each obtained by finding a local minimum of a potential energy function from a random starting point. The information from these conformers is then used to form a convex quadratic global underestimating...

In this paper, we study various supervised learning methods for training feed-forward neural networks. In general, such learning can be considered as a nonlinear global optimization problem in which the goal is to minimize a nonlinear error function that spans the space of weights using heuristic strategies that look for global optima (in contrast to local optima). We survey various global opti...