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11.
In this paper, we will propose algorithms for calculating a minimal ellipsoid circumscribing a polytope defined by a system
of linear inequalities. If we know all vertices of the polytope and its cardinality is not very large, we can solve the problem
in an efficient manner by a number of existent algorithms. However, when the polytope is defined by linear inequalities, these
algorithms may not work since the cardinality of vertices may be huge. Based on a fact that vertices determining an ellipsoid
are only a fraction of these vertices, we propose algorithms which iteratively calculate an ellipsoid which covers a subset
of vertices. Numerical experiment shows that these algorithms perform well for polytopes of dimension up to seven. 相似文献
12.
Mikhail Andramonov 《Journal of Global Optimization》2002,24(2):115-132
We consider applications of disjunctive programming to global optimization and problems with equilibrium constraints. We propose a modification of the algorithm of F. Beaumont for disjunctive programming problems and show its numerical efficiency. 相似文献
13.
Y. Wardi 《Journal of Optimization Theory and Applications》1989,61(3):473-485
A stochastic algorithm for finding stationary points of real-valued functions defined on a Euclidean space is analyzed. It is based on the Robbins-Monro stochastic approximation procedure. Gradient evaluations are done by means of Monte Carlo simulations. At each iteratex
i
, one sample point is drawn from an underlying probability space, based on which the gradient is approximated. The descent direction is against the approximation of the gradient, and the stepsize is 1/i. It is shown that, under broad conditions, w.p.1 if the sequence of iteratesx
1,x
2,...generated by the algorithm is bounded, then all of its accumulation points are stationary. 相似文献
14.
15.
We consider the problem of maximizing a linear fractional function on the Pareto efficient frontier of two other linear fractional functions. We present a finite pivoting-type algorithm that solves the maximization problem while computing simultaneously the efficient frontier. Application to multistage efficiency analysis is discussed. An example demonstrating the computational procedure is included. 相似文献
16.
许多实验对用CsI(Tl)闪烁晶体作为探测器来寻找和探测暗物质的可行性进行了研究.本工作利用8MeV单能中子轰击CsI(Tl)晶体探测器来研究Cs核和I核的QuenchingFactor.在数据处理中,运用脉冲形状甄别(PSD)方法来分辨反冲核信号和本底信号.实验结果表明,在7keV到132keV的能区中,Quench ingFactor随着反冲核能量的减少而增加.在探测暗物质的实验中,这一性质对于CsI(Tl)晶体探测器获得较低的能量阈值是很有利的. 相似文献
17.
We describe a new algorithm which uses the trajectories of a discrete dynamical system to sample the domain of an unconstrained objective function in search of global minima. The algorithm is unusually adept at avoiding nonoptimal local minima and successfully converging to a global minimum. Trajectories generated by the algorithm for objective functions with many local minima exhibit chaotic behavior, in the sense that they are extremely sensitive to changes in initial conditions and system parameters. In this context, chaos seems to have a beneficial effect: failure to converge to a global minimum from a given initial point can often be rectified by making arbitrarily small changes in the system parameters. 相似文献
18.
The annealing algorithm (Ref. 1) is modified to allow for noisy or imprecise measurements of the energy cost function. This is important when the energy cannot be measured exactly or when it is computationally expensive to do so. Under suitable conditions on the noise/imprecision, it is shown that the modified algorithm exhibits the same convergence in probability to the globally minimum energy states as the annealing algorithm (Ref. 2). Since the annealing algorithm will typically enter and exit the minimum energy states infinitely often with probability one, the minimum energy state visited by the annealing algorithm is usually tracked. The effect of using noisy or imprecise energy measurements on tracking the minimum energy state visited by the modified algorithms is examined.The research reported here has been supported under Contracts AFOSR-85-0227, DAAG-29-84-K-0005, and DAAL-03-86-K-0171 and a Purdue Research Initiation Grant. 相似文献
19.
20.
This paper is concerned with the implementation and testing of an algorithm for solving constrained least-squares problems. The algorithm is an adaptation to the least-squares case of sequential quadratic programming (SQP) trust-region methods for solving general constrained optimization problems. At each iteration, our local quadratic subproblem includes the use of the Gauss–Newton approximation but also encompasses a structured secant approximation along with tests of when to use this approximation. This method has been tested on a selection of standard problems. The results indicate that, for least-squares problems, the approach taken here is a viable alternative to standard general optimization methods such as the Byrd–Omojokun trust-region method and the Powell damped BFGS line search method. 相似文献