Global Optimization Algorithms as Statistical Decision Procedures — The Information Approach

2000 ◽  
pp. 53-125
Author(s):  
Roman G. Strongin ◽  
Yaroslav D. Sergeyev
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms ◽  
Decision Procedures ◽  
Statistical Decision ◽  
Information Approach

scholarly journals The Challenge for the Nature-inspired Global Optimization Algorithms: Non-symmetric Benchmark Functions

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Zheng-Ming Gao ◽  
Juan Zhao ◽  
Yu-Rong Hu ◽  
Hua-Feng Chen
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms

On hybridization of stochastic global optimization algorithms taking into account the features of their architecture

2021 ◽  
Vol 1 ◽  
pp. 113-117
Author(s):  
Dmitry Syedin ◽  
Keyword(s):  
Global Optimization ◽  
Stochastic Optimization ◽  
Optimization Algorithms ◽  
Stochastic Global Optimization ◽  
Stochastic Optimization Algorithms ◽  
Pca Algorithm

The work is devoted to the hybridization of stochastic global optimization algorithms depending on their architecture. The main methods of hybridization of stochastic optimization algorithms are listed. An example of hybridization of the algorithm is given, the modification of which became possible due to taking into account the characteristic architecture of the M-PCA algorithm.

Results of two global optimization algorithms applied to a problem in biomechanics

2010 ◽  
Author(s):  
Nicholas R. Radcliffe ◽  
David R. Easterling ◽  
Layne T. Watson ◽  
Michael L. Madigan ◽  
Kathleen A. Bieryla
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms

scholarly journals Analysis of Flood Storage Area Operations in Huai River Using 1D and 2D River Simulation Models Coupled with Global Optimization Algorithms

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 509 ◽  
Author(s):  
Andreja Jonoski ◽  
Ioana Popescu ◽  
Sun Zhe ◽  
Yuhan Mu ◽  
Yiqing He
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms ◽  
Local Population ◽  
Simulation Models ◽  
Flood Management ◽  
Nsga Ii ◽  
Operational Strategies ◽  
Huai River ◽  
Storage Area ◽  
Flood Storage

This article addresses the issue of flood management using four flood storage areas in the middle section of Huai River in China which protect the important downstream city of Bengbu. The same areas are also used by the local population as residential and agricultural zones. An optimization problem is therefore posed, with two objectives of simultaneously minimizing the downstream flood risk in Bengbu city and the storage areas’ economic damages. The methodology involved development of river flood models using HEC-RAS, with varying complexity, such as 1-dimensional (1D) model with storage areas represented as lumped conceptual reservoirs, and 2-dimensional (2D) models with detailed representation of the terrain, land-use and hydrodynamics in the storage areas. Experiments of coupling these models with global optimization algorithms (NSGA-II, PESA-II and SPEA-II) were performed (using the HEC-RAS Controller), in which the two objective functions were minimized, while using stage differences between the river and the storage areas as decision variables for controlling the opening/closing of the gates at the lateral structures that link the river with the storage areas. The comparative analysis of the results indicate that more refined optimal operational strategies that spread the damages across all storage areas can be obtained only with the detailed flood simulation models, regardless of the optimization algorithm used.

scholarly journals Analysis of Some Global Optimization Algorithms for Space Trajectory Design

2010 ◽  
Vol 47 (2) ◽  
pp. 334-344 ◽  
Author(s):  
M. Vasile ◽  
E. Minisci ◽  
M. Locatelli
Keyword(s):  
Global Optimization ◽  
Optimization Algorithms ◽  
Trajectory Design ◽  
Space Trajectory Design

Fixture Layout Design of Sheet Metal Parts Based on Global Optimization Algorithms

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
YanFeng Xing
Keyword(s):  
Finite Element ◽  
Global Optimization ◽  
Sheet Metal ◽  
Optimization Algorithms ◽  
Layout Optimization ◽  
Sheet Metal Parts ◽  
Fixture Layout ◽  
Fixture Layout Optimization ◽  
Dimensional Variation

Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated with a quantity of finite element (FE) analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3dcs simulation (for dimensional analyses) and global optimization algorithms. In this paper, two global algorithms are proposed to optimize fixture locator points, which are social radiation algorithm (SRA) and GAOT, a genetic algorithm (GA) in optimization toolbox in matlab. The flowchart of fixture design includes the following steps: (1) The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. (2) The two global optimization algorithms are edited to be used to optimize fixture schemes based on matlab. (3) Since matlab macrocommands of 3dcs have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the GAOT algorithm is more suitable than SRA for generating the optimal fixture layout with excellent efficiency for engineering applications.

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