Doyle J, Carlson JM
Control and Dynamical Systems, California Institute of Technology, Pasadena, California 91125, USA.
Phys Rev Lett. 2000 Jun 12;84(24):5656-9. doi: 10.1103/PhysRevLett.84.5656.
We introduce a family of robust design problems for complex systems in uncertain environments which are based on tradeoffs between resource allocations and losses. Optimized solutions yield the "robust, yet fragile" features of highly optimized tolerance and exhibit power law tails in the distributions of events for all but the special case of Shannon coding for data compression. In addition to data compression, we construct specific solutions for world wide web traffic and forest fires, and obtain excellent agreement with measured data.
我们针对不确定环境中的复杂系统引入了一类基于资源分配与损失权衡的稳健设计问题。优化后的解决方案展现出高度优化容限的“稳健却脆弱”特性，并且除了数据压缩的香农编码这种特殊情况外，在事件分布中呈现幂律尾部。除了数据压缩，我们还针对万维网流量和森林火灾构建了具体的解决方案，并与实测数据取得了极佳的吻合度。
