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Stochastic Derivative-Free Optimization on Riemannian Manifolds
In this chapter, the main algorithm of the book, Extended RSDFO, is described. The chapter begins by formalizing a generalized framework, Riemannian...
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A New Comparison Function Based Direct Multisearch Method for Derivative-Free Multi-objective Optimization Problems
In this paper, for addressing Multi-Objective Derivative-Free Optimization (MODFO) problems with box constraints, a new direct multisearch algorithm...
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Modelling architected plate using a non-local derivative-free shear deformable plate theory
The internal length scale relating to the cell size plays a crucial role in predicting the response of architected structures when subjected to...
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Modelling architected beam using a nonlocal derivative-free shear deformable beam theory
It has been well established that the internal length scale related to the cell size plays a critical role in the response of architected structures....
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Fundamentals of Numerical Optimization
This chapter summarizes fundamentals of numerical optimization. The material covered here is not supposed to be a systematic and exhaustive...
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A derivative-free memoryless BFGS hyperplane projection method for solving large-scale nonlinear monotone equations
In this work, by combining a three-term memoryless BFGS conjugate gradient direction with the hyperplane projection technique , we develop a new...
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A Derivative and Inversion-Free Quasi-Newton Power Flow for a Droop-Regulated Islanded AC Microgrid
The autonomous power-sharing among dispatchable sources in an islanded microgrid occurs due to a droop-control philosophy at the local control level....
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Collapse-resistance optimization of fabricated single-layer grid shell based on sequential approximate optimization
In this work, the surrogate model of the collapse load in terms of the structural morphology is established based on the radial basis function (RBF)...
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Distributed gradient-free and projection-free algorithm for stochastic constrained optimization
Distributed stochastic zeroth-order optimization (DSZO), in which the objective function is allocated over multiple agents and the derivative of cost...
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Research on Optimization of CCUS Injection Production Parameters in High-Temperature Reservoirs Based on Intelligent Optimization Algorithms
The paper takes the Jidong Nanbu high temperature oil reservoir as the research object and establishes the comprehensive numerical model of CO 2 ...
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Shape optimization of a snowboard sidecut geometry
The distribution of the contact pressure occurring under the edge of a snowboard during a carved turn is a key factor influencing the riding...
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Robust optimization design of a flying wing using adjoint and uncertainty-based aerodynamic optimization approach
Robust optimization design is significant and urgently required for the fly wings, owing to its unique characteristics. However, there is a lack of...
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Double Gradient Method: A New Optimization Method for the Trajectory Optimization Problem
In this paper, a new optimization method for the trajectory optimization problem is presented. This new method allows to predict racing lines...
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Topology Optimization
Topology optimization (TO) is a structural optimization method achieving the fundamental change of the structure. Although TO can generate innovative...
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Yet another parameter-free shape optimization method
The use of node coordinates as design variables in shape optimization offers a larger design space than computer-aided design (CAD)-based shape...
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Optimization
Optimization can be defined in various ways. Simplified perception of optimization as “the art of doing things best”.
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Multiobjective Optimization of Hull Form Based on Global Optimization Algorithm
Rankine source method, optimization technology, parametric modeling technology, and improved multiobjective optimization algorithm were combined to...
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Optimization Methods in General
As we have mentioned above, there is no one universal method for different types of optimization problems. We have a set of optimization methods...
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Empirical study of evolutionary computation-based multi-objective Bayesian optimization for materials discovery
Multi-objective Bayesian optimization (MOBO) is broadly used for applications with high cost observations such as materials discovery. In BO, a...
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Yield Optimization
We introduced the yield as the fraction of realizations in a manufacturing process fulfilling the performance feature specifications (PFS),...