多维空间中任意类属函数的多策略优化器
A multi-strategy optimizer for arbitrary generic functions in multidimensional space
摘要：
本文提出了一种算法，该算法能够为任意的多元通用函数找到一个可能的全局最优值（最小值）和一组次优点。该算法的目的是处理甚至与复杂的行为，不规则和嘈杂的功能，具有陡峭的变化，并表现出大量的局部次优点。必须处理有限域的复杂性，因为这是通常的情况下，考虑。该方法由多个级联阶段组成，每个阶段采用不同的策略来改进前一阶段的结果。在一个连贯的方案中重新阐述了已知方法中采用的许多想法和概念，并引入了几个新的想法。行最小化在大多数阶段中起着重要的作用，为此，还使用了一种新的强大的行最小化算法。
英文摘要：
An algorithm capable of finding a likely global optimum (minimum) and a set of sub-optimal points for arbitrary generic functions of several variables is presented. The algorithm is designed to deal even with functions of complex behavior, irregular and noisy, with steep variations and exhibiting a lot of local sub-optimal points. The complications of having to deal with a finite domain, as this is usually the case, are taken into account. The method is composed of a number of cascaded stages, each employing a different strategy to improve over the results of the previous stage. Many ideas and concepts employed in known methods are re-elaborated in a coherent scheme, plus several new ideas are introduced. Line minimization plays an important role in most stages, for this purpose a new and powerful algorithm for line minimization is used as well.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
