The global optimal solution to the three-dimensional layout optimization model with behavioral constraints

2004 ◽  
Vol 15 (1-2) ◽  
pp. 313-321 ◽  
Author(s):  
Tie Jun ◽  
Enmin Feng
Keyword(s):  
Optimization Model ◽  
Three Dimensional ◽  
Optimal Solution ◽  
Layout Optimization ◽  
Global Optimal Solution ◽  
Behavioral Constraints ◽  
Global Optimal

A Time-Stepping Scheme for Quasistatic Multibody Systems

2005 ◽  
Author(s):  
J. C. Trinkle ◽  
Stephen Berard ◽  
J. S. Pang
Keyword(s):  
Three Dimensional ◽  
Sufficient Conditions ◽  
Optimal Solution ◽  
Contact Forces ◽  
Global Optimal Solution ◽  
Convex Optimization Problem ◽  
Time Stepping ◽  
Global Optimal ◽  
Necessary And Sufficient ◽  
First Time

Two new instantaneous-time models for predicting the motion and contact forces of three-dimensional, quasistatic multi-rigid-body systems are developed; one linear and one nonlinear. The nonlinear characteristic is the result of retaining the usual quadratic friction cone in the model. Discrete-time versions of these models provide the first time-stepping methods for such systems. As a first step to understanding their usefulness in simulation and manipulation planning, a theorem defining the equivalence of solutions of a time-stepping method for the nonlinear model and a global optimal solution of a related convex optimization problem is given. In addition, a Proposition giving necessary and sufficient conditions for solution uniqueness of the nonlinear time-stepping method is given. Finally, a simple example is discussed to help develop intuition about quasistatic systems and to solidify the reader’s understanding of the theorem and proposition.

Optimal selection of precision points for function synthesis of spherical 4R linkage

2009 ◽  
Vol 223 (9) ◽  
pp. 2183-2189 ◽  
Author(s):  
Y Suixian ◽  
Y Hong ◽  
G Y Tian
Keyword(s):  
Optimization Model ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Scaling Factor ◽  
Optimal Selection ◽  
Global Optimal Solution ◽  
New Approach ◽  
Numerical Interpolation ◽  
Global Optimal ◽  
Selection Of

In order to reduce synthesis error, a new approach is reported to select precision points for function synthesis of spherical 4R linkages. Based on a closed-form symbolic solution of the set of function synthesis equations of spherical 4R linkages, the structure error equation has been derived by introducing a scaling factor. After this, an optimization model was constructed to search for the precision points. The initial solution of the optimization model was chosen using a numerical interpolation method. The global optimal solution was obtained using the fractal algorithm. To illustrate this, an example is presented and discussed before finally deriving conclusions.

Fuzzy Optimal Design of Tower Crane Jib

2011 ◽  
Vol 199-200 ◽  
pp. 530-533
Author(s):  
Xin Hua Li ◽  
Jian Zhou ◽  
Yi Zhang ◽  
Ling Dai
Keyword(s):  
Optimal Design ◽  
Optimization Model ◽  
Unique Feature ◽  
Optimal Solution ◽  
Amplification Coefficient ◽  
Constraint Condition ◽  
Global Optimal Solution ◽  
Tower Crane ◽  
Fuzzy Constraint ◽  
Global Optimal

This article takes the tower crane jib as the optimized object, in view of the jib unique feature, and has established the jib quality optimization objective function, then uses amplification coefficient to obtain its membership function to the fuzzy constraint condition,thus has transformed constraint condition very well. Direct searching tool-box of MATLAB software is adopted to get the optimization model,not only is simplified the optimization process,but also global optimal solution is found reliably.

A Smooth Clustering Algorithm Based on Parameter Free Filled Function

2010 ◽  
Vol 143-144 ◽  
pp. 389-393
Author(s):  
Qing Wu ◽  
Li Xing Yuan
Keyword(s):  
Optimization Model ◽  
Clustering Algorithm ◽  
Optimal Solution ◽  
Filled Function ◽  
Filled Function Method ◽  
Global Optimal Solution ◽  
Entropy Factor ◽  
Global Optimal ◽  
Clustering Center ◽  
Entropy Technique

In this paper, we propose an algorithm to find centers of clusters based on adjustable entropy technique. A completely differentiable non-convex optimization model for the clustering center problem is constructed. A parameter free filled function method is adopted to search for a global optimal solution of the optimization model. The proposed algorithm can avoid the numerical overflow phenomenon. Numerical results illustrate that the proposed algorithm can effectively hunt centers of clusters and especially improve the accuracy of the clustering even with a relatively small entropy factor.

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

scholarly journals Best Proximity Point Results in Complex Valued Metric Spaces

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Binayak S. Choudhury ◽  
Nikhilesh Metiya ◽  
Pranati Maity
Keyword(s):  
Minimum Distance ◽  
Metric Spaces ◽  
Optimal Solution ◽  
Global Optimal Solution ◽  
Complex Valued Metric Space ◽  
Fixed Point Equation ◽  
Point Equation ◽  
Global Optimal ◽  
Metric Function ◽  
Complex Valued

We introduce the concept of proximity points for nonself-mappings between two subsets of a complex valued metric space which is a recently introduced extension of metric spaces obtained by allowing the metric function to assume values from the field of complex numbers. We apply this concept to obtain the minimum distance between two subsets of the complex valued metric spaces. We treat the problem as that of finding the global optimal solution of a fixed point equation although the exact solution does not in general exist. We also define and use the concept of P-property in such spaces. Our results are illustrated with examples.

scholarly journals Prototype Filter Design Based on Channel Estimation for FBMC/OQAM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongjin Liu ◽  
Xihong Chen ◽  
Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Channel Estimation ◽  
Optimization Problem ◽  
Filter Design ◽  
Stop Band ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Global Optimal Solution ◽  
Prototype Filter ◽  
Global Optimal

A prototype filter design for FBMC/OQAM systems is proposed in this study. The influence of both the channel estimation and the stop-band energy is taken into account in this method. An efficient preamble structure is proposed to improve the performance of channel estimation and save the frequency spectral efficiency. The reciprocal of the signal-to-interference plus noise ratio (RSINR) is derived to measure the influence of the prototype filter on channel estimation. After that, the process of prototype filter design is formulated as an optimization problem with constraint on the RSINR. To accelerate the convergence and obtain global optimal solution, an improved genetic algorithm is proposed. Especially, the History Network and pruning operator are adopted in this improved genetic algorithm. Simulation results demonstrate the validity and efficiency of the prototype filter designed in this study.

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