Variable reduction for multi-objective optimization using data mining techniques; application to aerospace structures

Application of data mining in multiobjective optimization problems

“…And earlier in [4] the classification rules for evolutionary multiobjective Airfoil geometry modeled by S-plines [12,14] A. Mosavi: Int. J. Simul.…”

“…In mechanical engineering, the structural simulation is tightly integrated more than one discipline [10,13,14,15,16,22]. Meanwhile, the trend nowadays is to utilize independent computational codes for each discipline [20].…”

Application of data mining in multiobjective optimization problems

“…And earlier in [4] the classification rules for evolutionary multiobjective Airfoil geometry modeled by S-plines [12,14] A. Mosavi: Int. J. Simul.…”

“…In mechanical engineering, the structural simulation is tightly integrated more than one discipline [10,13,14,15,16,22]. Meanwhile, the trend nowadays is to utilize independent computational codes for each discipline [20].…”

Cycle flow formulation of optimal network flow problems and respective distributed solutions

“…Moreover, in [14] a new variable reduction techniques for IQP proposed which fixes some decision variables at zero without loosing optimality. In multiobjective optimization problems also it is shown that using data mining techniques it is possible to reduce less effective variables [15]. For evolutionary optimization problems, [16] presents how variable reduction techniques can be applied to obtain the variable relations from the partial derivatives of an optimization function.…”

Aeromechanical Optimization of First Row Compressor Test Stand Blades

“…Optimization of the axial turbomachinery as a prevalent activity in the enhancement ofthe efficiency of the blade commonly is performed in recent year. Using multi-disciplinary design optimization (MDO) [1], [2], [13][14][15] which found in the ANSYS Workbench as a new conventional method and other turbomachinery analysis modules, axial turbomachinery blade concept can approach to its best performance and mechanical properties. Geometrical parameters consisting of stack line position (thickness and Sweep angle) can be considered as our design variable to maximize stage characteristics.…”

Application of data mining in multiobjective optimization problems

“…And earlier in [4] the classification rules for evolutionary multiobjective Airfoil geometry modeled by S-plines [12,14] A. Mosavi: Int. J. Simul.…”

“…In mechanical engineering, the structural simulation is tightly integrated more than one discipline [10,13,14,15,16,22]. Meanwhile, the trend nowadays is to utilize independent computational codes for each discipline [20].…”

Cycle flow formulation of optimal network flow problems and respective distributed solutions

“…Moreover, in [14] a new variable reduction techniques for IQP proposed which fixes some decision variables at zero without loosing optimality. In multiobjective optimization problems also it is shown that using data mining techniques it is possible to reduce less effective variables [15]. For evolutionary optimization problems, [16] presents how variable reduction techniques can be applied to obtain the variable relations from the partial derivatives of an optimization function.…”

Aeromechanical Optimization of First Row Compressor Test Stand Blades

“…Optimization of the axial turbomachinery as a prevalent activity in the enhancement ofthe efficiency of the blade commonly is performed in recent year. Using multi-disciplinary design optimization (MDO) [1], [2], [13][14][15] which found in the ANSYS Workbench as a new conventional method and other turbomachinery analysis modules, axial turbomachinery blade concept can approach to its best performance and mechanical properties. Geometrical parameters consisting of stack line position (thickness and Sweep angle) can be considered as our design variable to maximize stage characteristics.…”

Application of data mining in multiobjective optimization problems

“…And earlier in [4] the classification rules for evolutionary multiobjective Airfoil geometry modeled by S-plines [12,14] A. Mosavi: Int. J. Simul.…”

“…In mechanical engineering, the structural simulation is tightly integrated more than one discipline [10,13,14,15,16,22]. Meanwhile, the trend nowadays is to utilize independent computational codes for each discipline [20].…”

Cycle flow formulation of optimal network flow problems and respective distributed solutions

“…Moreover, in [14] a new variable reduction techniques for IQP proposed which fixes some decision variables at zero without loosing optimality. In multiobjective optimization problems also it is shown that using data mining techniques it is possible to reduce less effective variables [15]. For evolutionary optimization problems, [16] presents how variable reduction techniques can be applied to obtain the variable relations from the partial derivatives of an optimization function.…”

Aeromechanical Optimization of First Row Compressor Test Stand Blades

“…Optimization of the axial turbomachinery as a prevalent activity in the enhancement ofthe efficiency of the blade commonly is performed in recent year. Using multi-disciplinary design optimization (MDO) [1], [2], [13][14][15] which found in the ANSYS Workbench as a new conventional method and other turbomachinery analysis modules, axial turbomachinery blade concept can approach to its best performance and mechanical properties. Geometrical parameters consisting of stack line position (thickness and Sweep angle) can be considered as our design variable to maximize stage characteristics.…”