Bi-objective decision making in global optimization based on statistical models
Bi-objective decision making in global optimization based on statistical models
复制标题
基于统计模型的全局优化双目标决策
DOI：
10.1007/s10898-018-0622-5
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发表时间：
2018
影响因子：
1.8
通讯作者：
J. Calvin
中科院分区：
文献类型：
--
作者：
A. Žilinskas;J. Calvin
考虑了一个全局优化问题，其中目标函数假设为“黑箱”和“昂贵”。利用目标函数的统计模型和不确定条件下的理性决策理论，从理论上证明了算法的有效性。搜索过程被定义为用于计算目标函数值的站点的双目标选择序列。结果表明，最大平均改进算法和最大改进概率算法是该方法的特例。
A global optimization problem is considered where the objective functions are assumed “black box” and “expensive”. An algorithm is theoretically substantiated using a statistical model of objective functions and the theory of rational decision making under uncertainty. The search process is defined as a sequence of bi-objective selections of sites for the computation of the objective function values. It is shown that two well known (the maximum average improvement, and the maximum improvement probability) algorithms are special cases of the proposed general approach.