A Web-Based Platform for Modular Design of Intelligent Instrument Based on Improved Genetic Algorithm

2011 ◽  
Vol 88-89 ◽  
pp. 291-295
Author(s):  
Jian Pan ◽  
Guo Hong Mao ◽  
Jin Xiang Dong
Keyword(s):  
Genetic Algorithm ◽  
Modular Design ◽  
Optimal Solutions ◽  
Improved Genetic Algorithm ◽  
Web Database ◽  
User Requirement ◽  
Web Based ◽  
Encoding Scheme ◽  
Intelligent Instrument ◽  
Selection Of

The design of new products is a creative work based on designer’s knowledge or experience. This paper develops a web-based design platform for intelligent instrument with the technology of Java and web database. It aims at offering near-optimal solutions of product design scheme that meets user requirement with the selection of module. An improved genetic algorithm with a binary encoding scheme is proposed to accomplish the selection of module more effectively.

Layout Design of Naval Gun Magazine Based on Improved GA

2009 ◽  
Vol 419-420 ◽  
pp. 669-672
Author(s):  
Wei Fu ◽  
Sheng Hai Hu ◽  
Yang Ge
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
System Reliability ◽  
Layout Design ◽  
Mutation Operator ◽  
Improved Genetic Algorithm ◽  
Encoding Scheme ◽  
Performance Constraints ◽  
Naval Gun ◽  
Polygon Method

In this paper a magazine layout optimization model with performance constraints is described and the objective function and its constraints of magazine layout are established. A multiobjective optimizations layout model based on polygon method is put forward. The model deals with a series of constraints such as geometry constraints, in-and-out point position optimization, magazine capacity and system reliability and safety. An improved genetic algorithm (GA) is proposed in this paper based on the new encoding scheme and logical mutation operator. The algorithm solved the problem of multiobjective layout design with performance constraints.

The Genetic Algorithm with Two Heuristic Rules for TSP

2013 ◽  
Vol 694-697 ◽  
pp. 2787-2793
Author(s):  
Yong Wang
Keyword(s):  
Genetic Algorithm ◽  
Optimal Solutions ◽  
Improved Genetic Algorithm ◽  
Heuristic Rules ◽  
Heuristic Rule ◽  
Hamiltonian Paths ◽  
Sequencing Problem ◽  
Discrete Manufacturing ◽  
Np Complete ◽  
Manufacturing Problems

Many complex discrete manufacturing problems, such as manufacturing sequencing problem or machine scheduling problem etc, can be converted into a general traveling salesman problem (TSP). TSP has been proven to be NP-complete. The genetic algorithm is improved with two heuristic rules for TSP. The first heuristic rule is the four vertices and three lines inequality. It is applied to the local Hamiltonian paths to generate the better solutions. The second heuristic rule is executed to reverse the local Hamiltonian paths, which generates new better solutions. The two heuristic rules coordinate with each other and they are merged into the optimization process of genetic algorithm to improve its performance. The computation results show that the improved genetic algorithm can find the near optimal solutions for most of the TSP instances.

scholarly journals An Integrated Method for Modular Design Based on Auto-Generated Multi-Attribute DSM and Improved Genetic Algorithm

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 48
Author(s):  
Shuai Wang ◽  
Zhongkai Li ◽  
Chao He ◽  
Dengzhuo Liu ◽  
Guangyu Zou
Keyword(s):  
Genetic Algorithm ◽  
Degrees Of Freedom ◽  
Modular Design ◽  
Product Information ◽  
Evaluation Criteria ◽  
Automatic Programming ◽  
Improved Genetic Algorithm ◽  
Modular Architecture ◽  
Integrated Method ◽  
Electromechanical Products

Modular architecture is very conducive to the development, maintenance, and upgrading of electromechanical products. In the initial stage of module division, the design structure matrix (DSM) is a crucial measure to concisely express the component relationship of electromechanical products through the visual symmetrical structure. However, product structure modeling, as a very important activity, was mostly carried out manually by engineers relying on experience in previous studies, which was inefficient and difficult to ensure the consistency of the model. To overcome these problems, an integrated method for modular design based on auto-generated multi-attribute DSM and improved genetic algorithm (GA) is presented. First, the product information extraction algorithm is designed based on the automatic programming structure provided by commercial CAD software, to obtain the assembly, degrees of freedom, and material information needed for modeling. Secondly, based on the evaluation criteria of product component correlation strength, the structural correlation DSM and material correlation DSM of components are established, respectively, and the comprehensive correlation DSM of products is obtained through weighting processing. Finally, the improved GA and the modularity evaluation index Q are used to complete the product module division and obtain the optimal modular granularity. Based on a model in published literature and a bicycle model, comparative studies are carried out to verify the effectiveness and practicality of the proposed method.

Research on Sitting Transformer Substations in Rural Areas Based on Improved Genetic Algorithm

2014 ◽  
Vol 490-491 ◽  
pp. 1652-1656
Author(s):  
Wei Li ◽  
Yi Huang ◽  
Fang Min Wang
Keyword(s):  
Genetic Algorithm ◽  
Rural Areas ◽  
Electric Heating ◽  
Power Network ◽  
Improved Genetic Algorithm ◽  
Power Load ◽  
Electricity Load ◽  
Process Of Urbanization ◽  
Grid Layout ◽  
Selection Of

The process of urbanization, Beijing faces a number of environmental problems. Especially in the last few years, there has been constantly sustained fog and haze, which makes the implementation of electric heating in rural areas gradually on the agenda. After the implementation of electric heating, the irrationality of the regional power grid layout will be further amplified. With the rapid growth of electricity load in the planning area, the requirement of the power supply grid reliability and power quality is also increasing. Therefore, on the basis of power load forecasting in consideration of the the electric heating, and based on the particularity of rural power network, we achieve the Huairou District substation site with the use of improved genetic algorithm. The results can provide reference for the selection of substation of the whole Beijing rural area.

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