2009
DOI: 10.1007/s00170-009-2035-6
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Machining fixture layout design using ant colony algorithm based continuous optimization method

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Cited by 84 publications
(41 citation statements)
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“…A comparison was made between both the algorithms on the basis of minimum objective function value, and it was found that ACA solutions are better than those of GA [28]. By applying ACA, Padmanaban et al [34] recently optimized the machining fixture layout to minimize the workpiece elastic deformation discrete-based and continuous-based optimization methods. The dynamic response of the workpiece with respect to machining and clamping forces was determined using FEM.…”
Section: Intelligent Approaches To Fixture Design Systemsmentioning
confidence: 99%
“…A comparison was made between both the algorithms on the basis of minimum objective function value, and it was found that ACA solutions are better than those of GA [28]. By applying ACA, Padmanaban et al [34] recently optimized the machining fixture layout to minimize the workpiece elastic deformation discrete-based and continuous-based optimization methods. The dynamic response of the workpiece with respect to machining and clamping forces was determined using FEM.…”
Section: Intelligent Approaches To Fixture Design Systemsmentioning
confidence: 99%
“…Similarly, with the help of FEA, Prabhaharan et al 22 presented a fixture layout optimization method that used GAs and ant colony algorithm (ACA) separately to decrease the dimensional and form errors. Padmanaban et al 23 applied the ACA-based discrete and continuous optimization methods coupled with FEA for the optimization of the fixture layout so that the elastic deformation of the workpiece is minimized. Xing 24 conducted the design and optimization of the sheet metal locating points based on the improved fruit fly optimization algorithm (IFOA).…”
Section: Introductionmentioning
confidence: 99%
“…Liu et al [3] determined the initial number and positions of the locators by adding locators on the datum plane at the position with the maximum deformation repeatedly until the deformation was reduced within the range of milling accuracy. Prabhaharan et al [4,5] presented the fixture layout optimization methods that used GA and ant colony algorithm (ACA) separately combined with FEA to reduce the dimensional and form errors of the deformable workpiece. Through employing FEA to compute the workpiece deformation for a given fixture layout, Dou et al [6] conducted the applications and comparisons of GA, improved GA, particle swarm optimization (PSO) and improved PSO for the fixture layout locating optimization to minimize the elastic deformation of the workpiece.…”
Section: Introductionmentioning
confidence: 99%