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Articles by Rong-Chang Chen
Total Records ( 4 ) for Rong-Chang Chen
  Chien-Che Huang , Ruey-Gwo Chung , Rong-Chang Chen , Tung-Shou Chen , Tzu-Ning Le , Chih-Jung Hsu and Ying-Chih Tsai
  The purpose of this study was to find a best combination of key training items. Companies are generally concerned about whether training can increase business performance and want to know what training items are crucial to enhancement of performance. Thus, there is a need to find the key training items. In this study, a combined scheme of Genetic Algorithms (GA) and Support Vector Machines (SVM) is employed to find the optimal combination of the key items. The data used are collected from some small and medium-sized enterprises and are from the database of the Bureau of Employment and Vocational Training (BEVT) in Taiwan. Results from this study show that an optimal combination of key items can be effectively found by using the proposed approach. When companies intend to successfully improve the business performance and cost-efficiently implement training, they can focus on the key training items.
  Yuan-Hung Kao , Tung-Shou Chen , Wei-Bin Lee , Rong-Chang Chen , Chien-Che Huang , Ming-Chang Lin and Yi-Lin Wang
  In Taiwan, the Government designed a system called Taiwan Train Quali System (TTQS), which helps the enterprises to build up a quality control and training system for strengthening their competition and rising up the performance. In order to help the enterprises to focus on the important assessment items, there were some researchers using the GA-SVM algorithm to find the key training items of TTQS for the business growth. However, those researches were only for the analysis result of all industries, also they were not have further consideration about the characteristics of the individual industry and the classification according as the turnover growth rates, which can not directly relate to the assessment result of TTQS. Thus, the proposed paper amended the analysis based on the TTQS assessment scores and also further aimed at the key training items of manufacturing, which decreases money wasting and speed up the efficiency training. According to the experimental results, the manufacturers should focuses on the training plan and its purpose, the training monitor and performance must be caution as well, to helping the enterprises can choose their priority items to modify by their industry characteristics.
  Fan-Wu Meng , Ke-Chou Chen , Kuo-Chuan Lin and Rong-Chang Chen
  The purpose of this study is to employ a systematic approach to optimize the scheduling of volleyball tournaments. Given the total number of teams in a tournament, the number of game days, the number of courts and the number of teams at each division and the required time blocks at each game day can be optimally obtained by using integer programming. In addition, the referees can be optimally assigned to their preferred times by using Genetic Algorithm (GA). Results from the experiments show that the proposed approach can produce good solutions efficiently.
  Rong-Chang Chen , Ting-Tsuen Chen and Wei-Luen Fang
  The purpose of this study is to employ a genetic algorithm to solve the assignment problem of external off-the-job training courses. External off-the-job training offers many benefits to enterprises and thus is considered as a competitive weapon for many companies. With such understanding, planning and offering suitable training programs to employees is crucial. In this study, GA is employed as an analytical tool to allocate training courses to employees. The allocation is decided by a system which takes the employees’ preferences as well as the fairness of the allocation into consideration. The use of GA in solving the problem shows that the complex problem can be well solved and suitable allocations can be made. In addition, the system constructed by our approach is also easy to use and can facilitate the allocation under many different kinds of scenarios of the company.
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