Improved Genetic Algorithms Based Optimal Design of The Shuangji River Aqueduct

2011 ◽  
Vol 201-203 ◽  
pp. 1288-1291
Author(s):  
Xin Li Bai ◽  
Wei Yu ◽  
Dan Fei Wang ◽  
Yuan Yuan Fan
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Structural Optimization ◽  
Large Scale ◽  
Hybrid Genetic Algorithm ◽  
Computer Software ◽  
Search Method ◽  
Discrete Variables ◽  
Original Design ◽  
Design Plan

The simple genetic algorithm (SGA) is taken as the global search method, and the traditional direct search method for mixed-discrete variables as the local search method. The improved (hybrid) genetic algorithm (IGA) is obtained by improving the SGA. And through the introduction of penalty constraints, the problem dealing with the constraints in GA is successfully resolved. A mathematical model for structural optimization of aqueduct is established, and computer software is developed for structural optimization of large-scale aqueduct based on IGA. Using this program, the Shuangji River aqueduct is optimized and Rectangle-sectioned aqueduct design plan is obtained. Compared with the original design plan, optimal design is very economical and was adopted by Design Institute.

Optimal Design of the Stiffener Penstock Structure in a Hydropower Station

2013 ◽  
Vol 438-439 ◽  
pp. 561-564
Author(s):  
Xin Li Bai ◽  
Qi Pei Jia ◽  
Hai Li Su
Keyword(s):  
Genetic Algorithm ◽  
Local Stability ◽  
Hybrid Genetic Algorithm ◽  
Optimization Methods ◽  
External Pressure ◽  
Search Method ◽  
Hydropower Station ◽  
Optimized Design ◽  
Original Design ◽  
Hydropower Stations

In order to optimize the stiffener penstock structure in hydropower stations, the simple genetic algorithm and the direct search method in traditional optimization methods were integrated, and a new hybrid genetic algorithm was obtained. A mathematical model of the stiffener penstock structure was established, and the constraint expressions were presented for global stability of the penstock under external pressure as well as the local stability of the stiffening ring. The corresponding program was developed and applied to a hydropower station. Results show that compared with the original design, the optimized design of rectangular stiffener rings reduces the penstock wall thickness by 8%, saving steel products 12.9%. The economic benefit of optimization is very considerable.

A Structure Optimization for Hooklift Arm Device Based on the Genetic Algorithm

2012 ◽  
Vol 455-456 ◽  
pp. 1504-1508
Author(s):  
Huan Ming Chen ◽  
Da Wei Liu
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Parameter Optimization ◽  
Structure Optimization ◽  
Optimization Method ◽  
Optimized Design ◽  
Design Decision ◽  
Original Design ◽  
Multi Objective ◽  
Engineering Constraint

Based on the theory of FEM, the hooklift arm is modeled with the FEM software, and the structure of the device is optimized with genetic algorithm in a multi-objective/multi-parameter optimization environment, which results in an optimal design decision of the hooklift arm device under the engineering constraint. Comparison between optimized design decision and original design decision shows that the optimization is correct and the proposed multi-objective/multi-parameter optimization method is effective in improving the hooklift arm device.

scholarly journals Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
I. Hameem Shanavas ◽  
R. K. Gnanamurthy
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithm ◽  
Design Automation ◽  
Large Scale ◽  
Hybrid Approach ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Physical Design ◽  
Silicon Area ◽  
Vlsi Physical Design

In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.

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