Using a genetic algorithm to define worst-best and best-worst options of a DEXi-type model: Application to the MASC model of cropping-system sustainability |
| |
Institution: | 1. School of Public Health, Nanjing Medical University, Nanjing 211166, PR China;2. Department of Urology, Huai''an Hospital Affiliated with Xuzhou Medical University, Huai''an 223002, PR China;3. Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, PR China;4. Department of Urology, The First People''s Hospital of Lianyungang, Lianyungang 222002, PR China;1. Lipid Research Laboratory, IIS-Fundacion Jimenez Diaz, Universidad Autónoma de Madrid, Madrid, Spain;2. Department of Pediatrics, IIS-Fundacion Jimenez Diaz, Madrid, Spain |
| |
Abstract: | DEXi-type models have been used recently to assess specific problems in agricultural systems and to assess cropping-system scenarios. Finding the set of the “worst-best” (lowest scores for basic attributes that lead to the highest score for the root attribute) and “best-worst” (highest scores for basic attributes that lead to the lowest score for the root attribute) options are of interest for improving current cropping systems. As DEXi-type models revealed a monotonicity property, we used a genetic algorithm to find these two sets. These sets are small and show that only a few attributes need to have low scores to reach the best-worst options or high scores to reach the worst-best options. These attributes are those with a high sensitivity index. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|