| Technical Name | Robust Optimization Methods with Industrial Applications | ||
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| Project Operator | National Chung-Hsieng University/National Kaohsiung University of Science and Technology/Metal Industries R&D Centre | ||
| Project Host | 周至宏、蔡進聰、劉東官、周阜毅、林崇田、楊柏遠 | ||
| Summary | The robust optimization methods combine the experimental design method with the evolutionary optimization algorithm to enhance the intelligent systematic reasoning ability of the evolutionary optimization algorithm in optimizing both numerical and combination problems. The proposed methods have been practically applied to solve some optimization problems encountered in both smart manufacturing and intelligent automation of industry. |
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| Scientific Breakthrough | About our robust optimization methods, (I) our technological breakthroughs of industrial applications are especially reported by the IEEE CIS development column； (II) according to the Thomson Reuters ISI Web of Knowledge, Essential Science Indicators, 4 international journal articles have also been listed as "Highly Cited Papers", of which 2 international journal papers are also listed as "Top Papers". |
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| Industrial Applicability | The proposed robust optimization methods have been applied to solve problems such as design optimization, process parameter optimization, production scheduling optimization, as well as online automatic search and parameter optimization encountered in smart manufacturing and industrial intelligent automation. |
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| Keyword | Robust Optimization Methods Industrial Applications Parameters Optimization of Manufacturing Process Production Scheduling Optimal Design of Control Systems Experimental Design Evolutionary Optimization Online Automatic Search and Parameter Optimization Design Optimization Uncertainties | ||
| Notes | |||
- Contact
- choujh@nkust.edu.tw
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