Multi-Level Design Optimization Using Global Monotonicity Analysis

1989 ◽  
Vol 111 (2) ◽  
pp. 259-263 ◽  
Author(s):  
S. Azarm ◽  
W.-C. Li
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Solution Procedure ◽  
Bottom Level ◽  
Optimization Framework ◽  
Multi Level ◽  
Level Design ◽  
Monotonicity Analysis

This paper describes application of global monotonicity analysis within a mutli-level design optimization framework. We present a general formulation and solution procedure, based on a bottom-level global monotonicity analysis, for a design optimization problem which is decomposed into three levels of subproblems. A well-known gear reducer example illustrates application of the method.

A Multi-Level Optimization-Based Design Procedure Using Global Monotonicity Analysis

1988 ◽  
Author(s):  
S. Azarm ◽  
W.-C. Li
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Design Procedure ◽  
Solution Procedure ◽  
Bottom Level ◽  
Multi Level ◽  
Monotonicity Analysis ◽  
Optimization Based Design

Abstract This paper describes application of global monotonicity analysis within a decomposition framework. We present a general formulation and solution procedure, based on a bottom-level global monotornicity analysis, for a design optimization problem which is decomposed into three levels of subproblems. A well-known gear reducer example illustrates application of the method.

Multidisciplinary Design Optimization of Modular Industrial Robots

2011 ◽  
Author(s):  
Mehdi Tarkian ◽  
Johan Persson ◽  
Johan O¨lvander ◽  
Xiaolong Feng
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Structural Strength ◽  
Computational Cost ◽  
Industrial Robots ◽  
Multidisciplinary Design ◽  
Geometry Model ◽  
Optimization Framework ◽  
Speed Up ◽  
Multi Level

This paper presents a multidisciplinary design optimization framework for modular industrial robots. An automated design framework, containing physics based high fidelity models for dynamic simulation and structural strength analyses are utilized and seamlessly integrated with a geometry model. The proposed framework utilizes well-established methods such as metamodeling and multi-level optimization in order to speed up the design optimization process. The contribution of the paper is to show that by applying a merger of well-established methods, the computational cost can be cut significantly, enabling search for truly novel concepts.

Optimality and Constrained Derivatives in Two-Level Design Optimization

1990 ◽  
Vol 112 (4) ◽  
pp. 563-568 ◽  
Author(s):  
S. Azarm ◽  
W.-C. Li
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Simple Approach ◽  
Problem Structure ◽  
Before And After ◽  
Level Problem ◽  
Level Design ◽  
Identification Of Active Constraints ◽  
Optimality Test

The objective of this paper is twofold. First, an optimality test is presented to show that the optimality conditions for a separable two-level design optimization problem before and after its decomposition are the same. Second, based on identification of active constraints and exploitation of problem structure, a simple approach for calculating the gradient of a “second-level” problem is presented. This gradient is an important piece of information which is needed for solution of two-level design optimization problems. Three examples are given to demonstrate applications of the approach.

Interactive Computing in the Application of Monotonicity Analysis to Design Optimization

1983 ◽  
Vol 105 (2) ◽  
pp. 181-186 ◽  
Author(s):  
J. Zhou ◽  
R. W. Mayne
Keyword(s):  
Computer Program ◽  
Design Optimization ◽  
Optimization Problem ◽  
Solution Process ◽  
Active Part ◽  
Computer Algorithm ◽  
Interactive Computing ◽  
Number Of Publications ◽  
Monotonicity Analysis

The use of monotonicity analysis in design optimization has been demonstrated in a number of publications in recent years. The purpose of this paper is to indicate the possibility of implementing the concepts of monotonicity analysis in a computer algorithm. The computer program makes the monotonicity decisions. The user is asked to adjust the optimization problem accordingly and takes an active part in the solution process.

Parameter Sensitivity Analysis in Two-Level Design Optimization

1990 ◽  
Vol 112 (3) ◽  
pp. 354-361 ◽  
Author(s):  
W.-C. Li ◽  
S. Azarm
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Optimization Problem ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Local Effects ◽  
Level Design ◽  
Small Change ◽  
Optimum Solution

Parameter sensitivity analysis of a two-level design optimization problem can be decomposed into two levels. In the first-level, the sensitivities of the subproblems are calculated separately. In the second-level, the sensitivities obtained for the first-level subproblems are coordinated to obtain the overall sensitivity information. Using this approach, we cannot only obtain the overall effect that a small change in a parameter has on the optimum solution of a problem (or system) but also its local effects on the subproblems (or subsystems). A simple two-bar truss example demonstrates the approach.

Parameter Sensitivity Analysis in Two-Level Design Optimization

1989 ◽  
Author(s):  
W.-C. Li ◽  
S. Azarm
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Optimization Problem ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Local Effects ◽  
Level Design ◽  
Small Change ◽  
Optimum Solution

Abstract Parameter sensitivity analysis of a two-level design optimization problem can be decomposed into two levels. In the first-level, the sensitivities of the subproblems are calculated separately. In the second-level, the sensitivities obtained for the first-level subproblems are co-ordinated to obtain the overall sensitivity information. Using this approach, we can not only obtain the overall effect that a small change in a parameter has on the optimum solution of a problem (or system) but also its local effects on the subproblems (or subsystems). A simple two-bar truss example demonstrates the approach.

scholarly journals Rotor Shape Multi-Level Design Optimization for Double-Stator Permanent Magnet Synchronous Motors

2019 ◽  
Vol 34 (3) ◽  
pp. 1223-1231 ◽  
Author(s):  
Pedram Asef ◽  
Ramon Bargallo Perpina ◽  
Saeed Moazami ◽  
Andrew Craig Lapthorn
Keyword(s):  
Design Optimization ◽  
Permanent Magnet ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors ◽  
Multi Level ◽  
Level Design ◽  
Rotor Shape

Optimality and Constrained Derivatives in Two-Level Design Optimization

1989 ◽  
Author(s):  
S. Azarm ◽  
W.-C. Li
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Simple Approach ◽  
Problem Structure ◽  
Before And After ◽  
Level Problem ◽  
Level Design ◽  
Identification Of Active Constraints ◽  
Optimality Test

Abstract The objective of this paper is twofold. First, an optimality test is presented to show that the optimality conditions for a two-level design optimization problem before and after its decomposition are the same. Second, based on identification of active constraints and exploitation of problem structure, a simple approach for calculating the gradient of a “second-level” problem is presented. This gradient is an important piece of information which is needed for solution of two-level design optimization problems. Three examples are given to demonstrate applications of the approach.

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