Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm
In order to solve the problems associated with the organization of the dynamic facility layout in a manufacturing workshop, utilizing a chaotic generic algorithm with improved Tent mapping is proposed as a solution. The tent map is used to generate the initial population which is distributed through...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2019-01-01
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| Series: | Production and Manufacturing Research: An Open Access Journal |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21693277.2019.1602486 |
| _version_ | 1831601057941159936 |
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| author | Xiaoxiao Wei Sicong Yuan Yuanqin Ye |
| author_facet | Xiaoxiao Wei Sicong Yuan Yuanqin Ye |
| author_sort | Xiaoxiao Wei |
| collection | DOAJ |
| description | In order to solve the problems associated with the organization of the dynamic facility layout in a manufacturing workshop, utilizing a chaotic generic algorithm with improved Tent mapping is proposed as a solution. The tent map is used to generate the initial population which is distributed throughout the solution space. Excellent individuals have the Genetic Algorithm optimization with elitist strategy applied to them. Partially matched crossover and mutation operations for single-period-layout encoding string are executed, and adaptive chaotic disturbance is increased to the superior individual. This method is an important innovation in the field of layout optimization by chaotic genetic algorithm. Finally, the paper compares several algorithms by analyzing sample outcomes of their respective implementations. It is also more convenient to verify the T-CGA method, which is better than the traditional method in solving the accuracy and the efficiency. |
| first_indexed | 2024-12-18T14:55:54Z |
| format | Article |
| id | doaj.art-47eb840a73c1424da563a8d0aa201388 |
| institution | Directory Open Access Journal |
| issn | 2169-3277 |
| language | English |
| last_indexed | 2024-12-18T14:55:54Z |
| publishDate | 2019-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Production and Manufacturing Research: An Open Access Journal |
| spelling | doaj.art-47eb840a73c1424da563a8d0aa2013882022-12-21T21:04:04ZengTaylor & Francis GroupProduction and Manufacturing Research: An Open Access Journal2169-32772019-01-017110912410.1080/21693277.2019.16024861602486Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithmXiaoxiao Wei0Sicong Yuan1Yuanqin Ye2Xi‘an University of Architecture and TechnologyXi‘an University of Architecture and TechnologyXi‘an University of Architecture and TechnologyIn order to solve the problems associated with the organization of the dynamic facility layout in a manufacturing workshop, utilizing a chaotic generic algorithm with improved Tent mapping is proposed as a solution. The tent map is used to generate the initial population which is distributed throughout the solution space. Excellent individuals have the Genetic Algorithm optimization with elitist strategy applied to them. Partially matched crossover and mutation operations for single-period-layout encoding string are executed, and adaptive chaotic disturbance is increased to the superior individual. This method is an important innovation in the field of layout optimization by chaotic genetic algorithm. Finally, the paper compares several algorithms by analyzing sample outcomes of their respective implementations. It is also more convenient to verify the T-CGA method, which is better than the traditional method in solving the accuracy and the efficiency.http://dx.doi.org/10.1080/21693277.2019.1602486cgadflpmulti-objective optimizationpartheno genetic algorithm |
| spellingShingle | Xiaoxiao Wei Sicong Yuan Yuanqin Ye Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm Production and Manufacturing Research: An Open Access Journal cga dflp multi-objective optimization partheno genetic algorithm |
| title | Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| title_full | Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| title_fullStr | Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| title_full_unstemmed | Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| title_short | Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| title_sort | optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm |
| topic | cga dflp multi-objective optimization partheno genetic algorithm |
| url | http://dx.doi.org/10.1080/21693277.2019.1602486 |
| work_keys_str_mv | AT xiaoxiaowei optimizingfacilitylayoutplanningforreconfigurablemanufacturingsystembasedonchaosgeneticalgorithm AT sicongyuan optimizingfacilitylayoutplanningforreconfigurablemanufacturingsystembasedonchaosgeneticalgorithm AT yuanqinye optimizingfacilitylayoutplanningforreconfigurablemanufacturingsystembasedonchaosgeneticalgorithm |