论文标题
混合整数约束多目标非平滑优化的无衍生化方法
A derivative-free approach to mixed integer constrained multiobjective nonsmooth optimization
论文作者
论文摘要
在这项工作中，我们考虑了对变量和一般非线性约束的多个约束性优化问题，其中仅通过查询黑匣子才能获得目标和约束函数值。此外，我们考虑了变量的子集只能采用整数值的情况。我们提出了一种基于新线路搜索的解决方案方法，并表明它会收敛到该问题的一组固定点。对于涉及连续变量的原因，我们采用策略来估算文献中最近提出的帕累托边境，并利用搜索方向的密集序列。必须假定离散值的变量子集使用适当修改的原始方向来处理以考虑多个目标函数的存在。用建议的方法在一组测试问题上获得的数值结果，并与其他溶液方法进行比较显示了所提出方法的生存能力和效率。
In this work, we consider multiobjective optimization problems with both bound constraints on the variables and general nonlinear constraints, where objective and constraint function values can only be obtained by querying a black box. Furthermore, we consider the case where a subset of the variables can only take integer values. We propose a new linesearch-based solution method and show that it converges to a set of stationary points for the problem. For what concerns the continuous variables, we employ a strategy for the estimation of the Pareto frontier recently proposed in the literature and which takes advantage of dense sequences of search directions. The subset of variables that must assume discrete values are dealt with using primitive directions appropriately modified to take into account the presence of more than one objective functions. Numerical results obtained with the proposed method on a set of test problems and comparison with other solution methods show the viability and efficiency of the proposed approach.
