Topic
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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TL;DR: This paper presents two polynomial-time approximation algorithms for MinWCVCP3, and shows that its approximation ratio is at most ln δ max + 4 + ln 2 , where δmax is the maximum degree of the graph.
11 citations
TL;DR: This paper is concerned with the minimum weight design of structures using Finite Element Analysis (FEA) and a new evolutionary structural optimization (ESO) algorithm is presented that exploits the movements of the nodes in an unstructured finite element mesh in an appropriate way.
Abstract: This paper is concerned with the minimum weight design of structures using Finite Element Analysis (FEA). A new evolutionary structural optimization (ESO) algorithm is presented. This method departs from previous studies of ESO in that it exploits the movements of the nodes in an unstructured finite element mesh in an appropriate way. An attractive feature of the scheme presented is that it carries out topology optimization in the interior of the domain concurrently with shape optimization of the exterior of the domain. Circular cavities are inserted into the interior of the domain from which the internal topology is then revealed by migration of the cavity edge nodes. Due to the complexity of the resulting cavity geometry the FE mesh tends to be refined internally. A scheme for maintaining a roughly uniform density unstructured finite element mesh throughout the optimization in a two-dimensional domain is presented. The designs produced posses smooth internal and external boundaries. The method uses iterative finite element analysis and re-meshing to correct for any element distortion. The benchmark "Michell Arch" problem is used to demonstrate the approach.
11 citations
02 Nov 2019
TL;DR: In this article, the authors considered the weight minimization of a spur gear train as an objective function and compared the results obtained using the Rao algorithm with other advanced optimization algorithms in previous studies such as particle swarm optimization (PSO), GA, simulated annealing (SA), and grey wolf optimizer (GWO).
Abstract: In many power transmission high-performance applications, the weight of the gear train is required to be minimized. The weight minimization of a spur gear train as an objective function is considered in this work. This problem contains six mixed type design variables such as four continuous variables, one discrete variable, and one integer variable. The optimum design of this gear train is verified with eight non-linear design constraints. In this work, a spur gear train problem is solved for two different sets of design variables’ ranges. Each design of a gear train obtained using the recently proposed Rao algorithms is compared with the designs obtained using other advanced optimization algorithms in previous studies such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), and grey wolf optimizer (GWO). The comparison revealed that the Rao algorithms gave better designs of the spur gear train with minimum weight.
11 citations
TL;DR: In this paper, an optimization technique that uses a real-coded genetic algorithm is applied to search for the optimum topography of a steel portal frame for a building and the result of a parametric study that investigates the effect of typical wind zones in Australia on the optimum parameters of building geometry is presented.
11 citations
TL;DR: In this paper, a minimum weight structure of variable geometry is formulated by the use of optimality criteria to express the member sizes in terms of the configurational variables satisfying the imposed constraints, thus enabling the merit function (weight) to become a nonlinear function of these variables alone.
11 citations