约束多目标优化问题包含多个目标函数和多种类型的约束条件，是一类广泛存在于科学和实际工程领域中的优化问题。基于进化算法求解无约束多目标优化问题和约束单目标优化问题已经得到了深入研究。然而，目前进化约束多目标优化却没有引起研究人员的足够重视。究其原因，主要是由于在求解约束多目标优化问题时，需要同时处理多种类型的约束条件和优化多个目标函数，这对进化算法提出了重大挑战。本项目拟对进化约束多目标优化领域展开全面研究，包括：1）构造具有多面特征的约束多目标优化测试函数集，为算法测试提供标准平台；2）设计合理的性能指标，用于评估进化算法求解约束多目标优化问题的性能；3）开发新的约束多目标进化算法，实现约束条件和目标函数的均衡；4）将基于偏好的多目标优化问题转换为约束多目标优化问题，降低求解难度；5）将所开发的算法应用于实际工程。通过对以上五个方面进行研究，本项目将进一步推动进化约束多目标优化领域的发展。

Constrained multiobjective optimization problems (CMOPs) include multiple objective functions and various constraints, which are frequently encountered in many science and engineering disciplines. Much effort has been made to solve unconstrained multiobjective optimization problems and constrained single-objective optimization problems by evolutionary algorithms (EAs). However, very few attempts have been made to investigate evolutionary constrained multiobjective optimization. The main reason is that when solving CMOPs, it is necessary to deal with various constraints and optimize multiple objective functions simultaneously, which poses a grand challenge to the current EAs. In this project, we will carry out extensive research on the field of evolutionary constrained multiobjective optimization. Firstly, we will construct a set of constrained multiobjective optimization test functions with multi-facet characteristics, which can provide a standard platform for testing the performance of a method. Secondly, we intend to design suitable performance indicators to evaluate the performance of EAs for CMOPs. Thirdly, new constrained multiobjective EAs will be developed to achieve the tradeoff between constraints and objective functions. Fourthly, we attempt to transform the preference based multiobjective optimization problems into CMOPs, with the purpose of reducing the difficulty of solving. Finally, applying the developed algorithms to deal with CMOPs in real-world engineering is also one major part of this project. By studying on the aforementioned five aspects, this project aims at further promoting the development of the field of evolutionary constrained multiobjective optimization.