scholarly journals OPTIMIZATION OF GRILLAGES USING GENETIC ALGORITHMS FOR INTEGRATING MATLAB AND FORTRAN ENVIRONMENTS / MATLAB IR FORTRAN APLINKŲ SUJUNGIMAS ROSTVERKAMS OPTIMIZUOTI GENETINIAIS ALGORITMAIS

2013 ◽  
Vol 6 (4) ◽  
pp. 564-568
Author(s):  
Darius Mačiūnas ◽  
Juozas Kauna ◽  
Dmitrij Šešok
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Optimal Layout ◽  
Reactive Force ◽  
Topology Optimization Problem ◽  
Original Algorithm ◽  
Fortran Programming Language

The purpose of the paper is to present technology applied for the global optimization of grillage-type pile foundations (further grillages). The goal of optimization is to obtain the optimal layout of pile placement in the grillages. The problem can be categorized as a topology optimization problem. The objective function is comprised of maximum reactive force emerging in a pile. The reactive force is minimized during the procedure of optimization during which variables enclose the positions of piles beneath connecting beams. Reactive forces in all piles are computed utilizing an original algorithm implemented in the Fortran programming language. The algorithm is integrated into the MatLab environment where the optimization procedure is executed utilizing a genetic algorithm. The article also describes technology enabling the integration of MatLab and Fortran environments. The authors seek to evaluate the quality of a solution to the problem analyzing experimental results obtained applying the proposed technology. Santrauka Straipsnyje pateikiama sijynų tipo pamatų (toliau sijynų) globalaus optimizavimo technologija. Optimizavimo tikslas – nustatyti optimalų polių išdėstymą sijynuose. Šis uždavinys priskiriamas topologijos optimizavimo uždavinių grupei. Tikslo funkciją sudaro maksimali poliuje kylanti atraminė reakcijos jėga, kuri minimizuojama optimizavimo procese. Šio uždavinio projektavimo kintamieji - polių padėtys po jungiančiosiomis sijyno sijomis. Tiesioginis reakcijų poliuose skaičiavimo uždavinys sprendžiamas originaliu algoritmu, sukurtu Fortran programavimo kalba. Šis algoritmas juodosios dėžės principu jungiamas prie MatLab aplinkos, kurioje genetiniu algoritmu sprendžiamas optimizavimo uždavinys. Straipsnyje taip pat aprašyta technologija, kuri leidžia sujungti Matlab ir Fortran aplinkas, t. y. iš Matlab aplinkos iškviesti Fortran paprogramį. Analizuodami eksperimentinius duomenis autoriai bando įvertinti gaunamų sprendinių kokybę.

scholarly journals Composite Differential Search Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Bo Liu
Keyword(s):  
Convergence Rate ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Control Parameters ◽  
Original Algorithm ◽  
New Space ◽  
Random Method ◽  
Better Than

Differential search algorithm (DS) is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS) is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

Modeling of a Controlled Service Platform: Proposals for an Optimal Layout

1996 ◽  
Author(s):  
H. Eschenauer ◽  
P. Neuser
Keyword(s):  
Optimization Problem ◽  
Optimization Procedure ◽  
Optimal Layout ◽  
Fe Method ◽  
Service Platform ◽  
System Reduction ◽  
Extreme Load ◽  
Structural Responses ◽  
Improved Design ◽  
Structural Optimization Problem

Abstract As an example of complex systems a controlled service platform is treated, for which an improved design has to be determined. Two substitute models that simplify the real system to a different degree are employed for the calculation of the structural responses by means of the Finite-Element (FE)-Method. The structural analyses are limited to the consideration of the system’s free vibration behaviour, as well as the displacements and stresses in an extreme load case, called bumper impact. A further system reduction is achieved by using sub-structuring and the reduction according to Guyan. The structural optimization problem is solved by means of the optimization procedure SAPOP that is based on the so-called Three-Columns-Concept. Results are given for a design optimized with respect to mass, first eigenfrequency, and stress.

Measurement of projectile’s in-bore yaw based on the optical lever principle

2017 ◽  
Vol 232 (12) ◽  
pp. 2378-2394 ◽  
Author(s):  
Qinbo Zhou ◽  
Xiaoting Rui ◽  
Fufeng Yang ◽  
Guoping Wang ◽  
Tianxiong Tu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Ray Tracing ◽  
Measurement System ◽  
Optimization Problem ◽  
Linear Time ◽  
Optimal Layout ◽  
Linear Time Invariant ◽  
Optical Lever ◽  
Time Invariant

The initial disturbance of a projectile emerging from the gun muzzle is a major reason for the projectile dispersion. Therefore, measurements of initial disturbances have a great value in improving the understanding. This paper establishes a mathematical model of the measurement system for the projectile’s in-bore orientation, by utilizing the theory of ray tracing and kinematics. The layout of the optical apparatuses is attributed to an optimization problem, and the genetic algorithm is implemented to acquire an optimal layout scheme, which is further verified by test. Also, the linear time-invariant characteristics of the measurement system are numerically verified in the context of spatial ray. These investigations will provide a technical support for the experiment, the optical apparatuses’ layout and calibration of the measurement system.

Research on the Application of College Automated Course Scheduling System Based on Genetic Algorithm

2013 ◽  
Vol 760-762 ◽  
pp. 1782-1785
Author(s):  
Xiu Ying Li ◽  
Dong Ju Du
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Teaching Quality ◽  
Combinatorial Optimization Problem ◽  
Scheduling System ◽  
Course Scheduling ◽  
Strong Ability

A reasonable curriculum contributes to the improvement of the training and teaching quality of college students. Using computer which is speed and strong ability to arrange curriculum automatically is imperative. Automatically curriculum arrangement is a constrained, multi-objective and intricate combinatorial optimization problem. Based on genetic algorithm of population search, it is suitable to process complex and nonlinear optimization problems which it difficult to solve for traditional search methods. In this paper solves complex automated course scheduling using genetic algorithms.

A genetic algorithm for a global optimization problem arising in the detection of gravitational waves

2010 ◽  
Vol 48 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Daniela di Serafino ◽  
Susana Gomez ◽  
Leopoldo Milano ◽  
Filippo Riccio ◽  
Gerardo Toraldo
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Gravitational Waves ◽  
Optimization Problem ◽  
Global Optimization Problem

Topology Optimization Design of Bars Structure Based on SKO Method

2013 ◽  
Vol 394 ◽  
pp. 515-520 ◽  
Author(s):  
Wen Jun Li ◽  
Qi Cai Zhou ◽  
Xu Hui Zhang ◽  
Xiao Lei Xiong ◽  
Jiong Zhao
Keyword(s):  
Global Optimization ◽  
Topology Optimization ◽  
Optimization Design ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Topology Optimization Problem ◽  
Proposed Model ◽  
Continuum Structure ◽  
The Impact

There are less topology optimization methods for bars structure than those for continuum structure. Bionic intelligent method is a powerful way to solve the topology optimization problems of bars structure since it is of good global optimization capacity and convenient for numerical calculation. This article presents a SKO topology optimization model for bars structure based on SKO (Soft Kill Option) method derived from adaptive growth rules of trees, bones, etc. The model has been applied to solve the topology optimization problem of a space frame. It uses three optimization strategies, which are constant, decreasing and increasing material removed rate. The impact on the optimization processes and results of different strategies are discussed, and the validity of the proposed model is proved.

scholarly journals Continuation Newton methods with deflation techniques and  quasi-genetic evolution for global optimization problems

2021 ◽  
Author(s):  
Xin-long Luo ◽  
Hang Xiao
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Newton Method ◽  
Stationary Point ◽  
Large Scale ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Stationary Points ◽  
Genetic Evolution

Abstract The global minimum point of an optimization problem is of interest in engineering fields and it is difficult to be solved, especially for a nonconvex large-scale optimization problem. In this article, we consider the continuation Newton method with the deflation technique and the quasi-genetic evolution for this problem. Firstly, we use the continuation Newton method with the deflation technique to find the stationary points from several determined initial points as many as possible. Then, we use those found stationary points as the initial evolutionary seeds of the quasi-genetic algorithm. After it evolves into several generations, we obtain a suboptimal point of the optimization problem. Finally, we use the continuation Newton method with this suboptimal point as the initial point to obtain the stationary point, and output the minimizer between this final stationary point and the found suboptimal point of the quasi-genetic algorithm. Finally, we compare it with the multi-start method (the built-in subroutine GlobalSearch.m of the MATLAB R2020a environment) and the differential evolution algorithm (the DE method, the subroutine de.m of the MATLAB Central File Exchange 2021), respectively. Numerical results show that the proposed method performs well for the large-scale global optimization problems, especially the problems of which are difficult to be solved by the known global optimization methods.

Firepower Assignment of Ship-to-Air Missile System

2014 ◽  
Vol 905 ◽  
pp. 702-705
Author(s):  
Yong Hong Lu ◽  
Ji Hua Dou ◽  
Xing Bao Yang ◽  
Chuan Wei Zhu
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Decision Support ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Hill Climbing ◽  
Unconstrained Optimization Problem ◽  
Provide Decision Support ◽  
Missile System ◽  
Standard Genetic Algorithm

Hybrid genetic algorithm has been proposed in this paper, which is proposed by combining standard genetic algorithm with hill climbing to solve the unconstrained optimization problem, which can get global optimization results of the firepower assignment, and provide decision support for the firepower assignment.

Perceptive Exploration of Layout Designs Using an Interactive Genetic Algorithm

2012 ◽  
Author(s):  
Julien Bénabès ◽  
Emilie Poirson ◽  
Fouad Bennis ◽  
Yannick Ravaut
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Subjective Evaluation ◽  
Performance Criteria ◽  
Final Decision ◽  
Complex Task ◽  
Optimal Layout ◽  
Interactive Genetic Algorithm ◽  
Qualitative Performance

Layout design optimization has a significant impact in the design and use of many engineering products and systems, such as the subdivision of a ship, the layout of facilities in a plant or further still the assembly of parts of a mechanism. The search for an optimal layout configuration is a critical and complex task due to the increasing demands of designers working on varied projects. A layout optimization process is generally divided into different steps: the description, formulation and solving of the problem and the final decision. This process consists in writing an optimization problem that transform designer’s requirements into variables, constraints and objectives. Then, an optimization algorithm has to be used in order to search for optimal solutions that fit with product’s specifications. This paper focuses on the last step which consists, for the designer, in making a choice on the solutions generated by the optimization algorithm. This choice is made according to the global performances of the designs and also the personal judgment of the designer. This judgment is based on the expertise of the designer and the subjective requirements that could not be integrated on the formulation of the problem. This paper proposes a perceptive exploration method, based on an Interactive Genetic Algorithm (IGA), used to explore designs, taking into account the subjective evaluation of the designer. The objective of this method is to select an ideal solution that realizes the best trade-off between the quantitative and qualitative performance criteria. This interactive process is tested on an industrial layout application which deals with the search for an optimal layout of facilities in a shelter.

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