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Minimum weight

About: Minimum weight is a research topic. Over the lifetime, 2002 publications have been published within this topic receiving 28244 citations.


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Journal ArticleDOI
TL;DR: The comparison shows that both the SQP and SAM-algorithms are able to converge to accurate minimum weight values, however, because of the lack of a guaranteed convergence property of the SAM method, it exhibits an inability to consistently converge to a fine tolerance.
Abstract: This paper presents a numerical performance comparison of a modern version of the well-established sequential quadratic programming (SQP) method and the more recent spherical approximation method (SAM). The comparison is based on the application of these algorithms to examples with nonlinear objective and constraint functions, among others: weight minimization problems in structural shape optimization. The comparison shows that both the SQP and SAM-algorithms are able to converge to accurate minimum weight values. However, because of the lack of a guaranteed convergence property of the SAM method, it exhibits an inability to consistently converge to a fine tolerance. This deficiency is manifested by the appearance of small oscillations in the neighbourhood of the solution.

11 citations

Journal ArticleDOI
TL;DR: An efficient method of using the dual simplex algorithm for finding minimum weight designs of stiff-jointed frameworks is described.

11 citations

Posted Content
TL;DR: In this article, a (l, s)-extension was proposed to extend the generator matrix of C by adding l columns with the property that at least s of the l letters added to each of the codewords of minimum weight in C are different from 0.
Abstract: We construct new linear codes with high minimum distance d. In at least 12 cases these codes improve the minimum distance of the previously known best linear codes for fixed parameters n,k. Among these new codes there is an optimal ternary [88,8,54] code. We develop an algorithm, which starts with already good codes C, i.e. codes with high minimum distance d for given length n and dimension k over the field GF(q). The algorithm is based on the newly defined (l,s)-extension. This is a generalization of the well-known method of adding a parity bit in the case of a binary linear code of odd minimum weight. (l,s)-extension tries to extend the generator matrix of C by adding l columns with the property that at least s of the l letters added to each of the codewords of minimum weight in C are different from 0. If one finds such columns the minimum distance of the extended code is d+s provided that the second smallest weight in C was at least d+s. The question whether such columns exist can be settled using a Diophantine system of equations.

11 citations

Journal ArticleDOI
TL;DR: A constant factor approximation algorithm is designed for MARPCP, which is much faster than the first method and shows an existing algorithm for MWDSP can produce an approximate solution forMARPCP.
Abstract: In this paper, we introduce a new clustering problem in underwater sensor networks, namely minimum average routing path clustering problem (MARPCP). To deal with the high complexity of MARPCP, we relax it to a special case of minimum weight dominating set problem (MWDSP). We show an existing algorithm for MWDSP can produce an approximate solution for MARPCP. Also, we design a constant factor approximation algorithm for MARPCP, which is much faster than the first method.

11 citations

Proceedings ArticleDOI
12 Jul 2008
TL;DR: This paper has successfully proposed the formulation of CM tracing user-defined paths based on the precision points by modifying the NSGA-II algorithm by incorporating a helper objective and a domain specific crossover which assist in generating a diverse set of non-dominated solutions.
Abstract: While designing the Compliant Mechanisms (CM), an equal attention is required on both the problem formulation and the optimization algorithm used. Authors of this paper have successfully proposed the formulation of CM tracing user-defined paths based on the precision points. In this paper, authors modify the NSGA-II algorithm by incorporating (i) a helper objective and (ii) a domain specific crossover which assist in generating a diverse set of non-dominated solutions. First, the single-objective optimization problem of minimizing the weight of structure is solved and named the topology as a reference design. Thereafter, a bi-objective optimization problem is dealt to evolve 'trade-off' solutions for a primary objective of minimizing the weight and a secondary objective of maximizing the diversity with respect to the reference design. Both the optimization problems are solved using a local search based NSGA-II procedure. This study has further compared its results with another GA implementation having a different crossover operator.

11 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202321
202239
202153
202051
201966
201858