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111.
We initiate the study of a new measure of approximation. This measure compares the performance of an approximation algorithm to the random assignment algorithm. This is a useful measure for optimization problems where the random assignment algorithm is known to give essentially the best possible polynomial time approximation. In this paper, we focus on this measure for the optimization problems Max‐Lin‐2 in which we need to maximize the number of satisfied linear equations in a system of linear equations modulo 2, and Max‐k‐Lin‐2, a special case of the above problem in which each equation has at most k variables. The main techniques we use, in our approximation algorithms and inapproximability results for this measure, are from Fourier analysis and derandomization. © 2004 Wiley Periodicals, Inc. Random Struct. Alg., 2004 相似文献
112.
L.G. Casado I. García T. Csendes V.G. Ruíz 《Journal of Optimization Theory and Applications》2003,118(1):27-43
Based on the investigation carried out in Ref. 1, this paper incorporates new studies about the properties of inclusion functions on subintervals while a branch-and-bound algorithm is solving global optimization problems. It is found that the relative place of the global minimum value within the inclusion function value of the objective function at the current interval indicates mostly whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a considerable amount of computation. Illustrative examples are discussed and an extended numerical study shows the advantages of the new approach. 相似文献
113.
114.
Arnold Neumaier 《Journal of Global Optimization》2003,25(2):175-181
A family of multivariate rational functions is constructed. It has strong local minimizers with prescribed function values at prescribed positions. While there might be additional local minima, such minima cannot be global. A second family of multivariate rational functions is given, having prescribed global minimizers and prescribed interpolating data. 相似文献
115.
116.
117.
The system design must be started from the concept with low cost and high performance. In this point, the topological shape of the structure is very important in the view of the structural rigidities and light-weight design.In this paper, the optimization methodology is presented in the design stage of the large optical mirror. We obtain the optimal layout through the topology optimization and then design the details through the size or shape optimization for structural rigidity. 相似文献
118.
Andrea Grosso Marco Locatelli Fabio Schoen 《Computational Optimization and Applications》2007,38(3):351-370
In this paper we perform a computational analysis of a population based approach for global optimization, Population Basin
Hopping (PBH), which was proven to be very efficient on very challenging global optimization problems by the authors (see
). The experimental analysis aims at understanding more deeply how the approach works and why it is successful on challenging
problems. 相似文献
119.
Linear mixed 0–1 integer programming problems may be reformulated as equivalent continuous bilevel linear programming (BLP)
problems. We exploit these equivalences to transpose the concept of mixed 0–1 Gomory cuts to BLP. The first phase of our new
algorithm generates Gomory-like cuts. The second phase consists of a branch-and-bound procedure to ensure finite termination
with a global optimal solution. Different features of the algorithm, in particular, the cut selection and branching criteria
are studied in details. We propose also a set of algorithmic tests and procedures to improve the method. Finally, we illustrate
the performance through numerical experiments. Our algorithm outperforms pure branch-and-bound when tested on a series of
randomly generated problems.
Work of the authors was partially supported by FCAR, MITACS and NSERC grants. 相似文献
120.
Discrete global descent method for discrete global optimization and nonlinear integer programming 总被引:2,自引:0,他引:2
A novel method, entitled the discrete global descent method, is developed in this paper to solve discrete global optimization
problems and nonlinear integer programming problems. This method moves from one discrete minimizer of the objective function
f to another better one at each iteration with the help of an auxiliary function, entitled the discrete global descent function.
The discrete global descent function guarantees that its discrete minimizers coincide with the better discrete minimizers
of f under some standard assumptions. This property also ensures that a better discrete minimizer of f can be found by some classical local search methods. Numerical experiments on several test problems with up to 100 integer
variables and up to 1.38 × 10104 feasible points have demonstrated the applicability and efficiency of the proposed method. 相似文献