| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1002/cplx.21742 |
| Optimizing the initial setting of complex adaptive systems-optimizing the layout of initial AFVs stations for maximizing the diffusion of AFVs. | |
| Zhao J; Ma T | |
| 发表日期 | 2016 |
| 出处 | Complexity 21 (1): 275-290 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | There are occasions when people want to optimize the initial setting of a CAS (complex adaptive system) so that it evolves in a desired direction. A CAS evolves by heterogeneous actors interacting with each other. It is difficult to describe the evolution process with an objective function. Researchers usually attempt to optimize an intervening objective function, which is supposed to help a CAS evolve in a desired direction. This article puts forward an approach to optimize the initial setting of a CAS dirctly (instead of through an intervening objective function) by nesting agent-based simulations in a genetic algorithm. In the approach, an intial setting of a CAS is treated as a genome, and its fitness is defined by the closeness between the simulation result and the desired evolution. We test the applicability of the proposed approach on the problem of optimizing the layout of initial AFV (alternative fuel vehicle) refueling stations to maximize the diffusion of AFVs. Computation experiments show that the initial setting generated with the approach would better induce the desired evolving result than optimizing an intervening objective function. The idea of the approach can also be applied to other decision making associated with a complex adaptive process. |
| 主题 | Transitions to New Technologies (TNT) |
| 关键词 | optimization complex adaptive system agent-based simulations layout initial AFV refueling station |
| URL | http://pure.iiasa.ac.at/id/eprint/11270/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130719 |
| 推荐引用方式 GB/T 7714 | Zhao J,Ma T. Optimizing the initial setting of complex adaptive systems-optimizing the layout of initial AFVs stations for maximizing the diffusion of AFVs.. 2016. |
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