论文标题
整体全球最佳条件和多物原理问题的算法
Integral Global Optimality Conditions and an Algorithm for Multiobjective Problems
论文作者
论文摘要
在这项工作中，我们为多目标问题提供了不可或缺的全球最佳条件，不一定是可区分的。已经以单个客观问题而闻名的积分表征通过加权总和和Chebyshev加权标量扩展到多目标问题。使用这个最后的标量化，我们提出了一种算法，用于获得弱帕累托前沿的近似值，该算法通过求解了多个多目标测试问题的集合来说明其有效性。
In this work, we propose integral global optimality conditions for multiobjective problems not necessarily differentiable. The integral characterization, already known for single objective problems, are extended to multiobjective problems by weighted sum and Chebyshev weighted scalarizations. Using this last scalarization, we propose an algorithm for obtaining an approximation of the weak Pareto front whose effectiveness is illustrated by solving a collection of multiobjective test problems.
