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Open AccessJournal ArticleDOI

Adjoint Variable Method for Multi-Objective Sizing and Shape Optimization

TLDR
In this paper, the adjoint variable method was used to reduce the number of sensitivity calculations for structural sizing and shape optimization problems, which can be used to solve multi-objective structural sizing problems efficiently.
Abstract
With smooth objective functions and constraint conditions, gradient-based methods can be used to solve multi-objective optimization problems efficiently. However, when applied to structural sizing optimization problems, using the Finite Element Method (FEM) and a finite difference scheme to calculate sensitivities can be computationally expensive. The adjoint variable method can be used to reduce computational cost. In order to solve multi-objective structural sizing and shape optimization problems efficiently, this paper proposes using the adjoint variable method. The adjoint variable method efficiently calculates multiple sensitivities for objectives that involve structural responses and cuts down computational cost by reducing the number of sensitivity calculations required per design variable.

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Citations
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Journal ArticleDOI

Multi-Objective Optimization of a Transonic Compressor Rotor by Using an Adjoint Method

TL;DR: In this article, the authors proposed a multi-objective optimization method based on the adjoint method to increase the total pressure ratio and the adiabatic efficiency of an aircraft engine.
Journal ArticleDOI

Multi-Objective Shape Optimization in Forced Heat-Convection Fields

TL;DR: In this article, a multi-objective shape optimization problem using normalized objective functional is formulated for the total dissipated energy minimization problem and the temperature distribution prescribed problem in steady heat-convection fields.
Proceedings ArticleDOI

Multi-Objective Design Optimization of a Transonic Compressor Rotor Using an Adjoint Equation Method

TL;DR: In this paper, a viscous adjoint method is applied to the multi-objective design optimization of a transonic compressor rotor blade row, and the results are presented in detail and the effects of blade profile modification on performance improvement and shock/tip-leakage interaction are examined.
References
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Journal ArticleDOI

Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art

TL;DR: The intent is to rigorously define multiobjective optimization problems and certain related concepts, present an MOEA classification scheme, and evaluate the variety of contemporary MOEAs.
Journal ArticleDOI

Adaptive weighted-sum method for bi-objective optimization: Pareto front generation

TL;DR: This paper presents a new method that effectively determines a Pareto front for bi-objective optimization with potential application to multiple objectives by changing the weights adaptively rather than by using a priori weight selections and by specifying additional inequality constraints.
Journal ArticleDOI

Multiobjective optimization of trusses using genetic algorithms

TL;DR: Using the concept of min–max optimum, a new GA-based multiobjective optimization technique is proposed and two truss design problems are solved using it, proving that this technique generates better trade-offs and that the genetic algorithm can be used as a reliable numerical optimization tool.
Journal ArticleDOI

Structural optimization using evolutionary algorithms

TL;DR: Modified versions of the basic EA are implemented to improve the performance of the optimization procedure and the numerical tests presented demonstrate the computational advantages of the discussed methods, which become more pronounced in large-scale optimization problems.
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