用Stenchweiler集成搜索算法求解全局优化问题的常数时间解
Constant-time solution to the Global Optimization Problem using Bruschweiler's ensemble search algorithm
摘要：
利用集成算法获得了连续全局优化问题的常时间解。我们表明，在一定的假设下，解决方案可以保证通过映射到一个离散的未排序的搜索问题的GOP，因此，Escherichweiler的合奏搜索算法。对于足够的测量技术的灵敏度，集成搜索算法的查询复杂度线性依赖于函数的域的大小。最终NMR实现的优点和局限性进行了讨论。
英文摘要：
A constant-time solution of the continuous Global Optimization Problem (GOP) is obtained by using an ensemble algorithm. We show that under certain assumptions, the solution can be guaranteed by mapping the GOP onto a discrete unsorted search problem, whereupon Bruschweiler's ensemble search algorithm is applied. For adequate sensitivities of the measurement technique, the query complexity of the ensemble search algorithm depends linearly on the size of the function's domain. Advantages and limitations of an eventual NMR implementation are discussed.
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