Multi-objective optimization problems (MOOPs) involve optimizing two or more conflicting objectives simultaneously. These problems are prevalent in various fields, including engineering ...

In datasets where identifying Pareto-optimal points is essential, deterministic algorithms like Simple Cull can be effective. However, as dataset size increases, these algorithms become less efficient ...

参考了知乎文章，写的很详细，那里是一个单目标的有向无环图最短路例子 https://zhuanlan.zhihu.com/p/81749290 ...

This chapter focuses on problems of large scale multi‐objective optimization problems (LSMOPs) and large scale many‐objective optimization problems. It refers to research adopting evolutionary ...

Large‐scale multi‐objective optimization problems (LSMOPs) refer to a subset of optimization problems which have both a large number of decision variables and multiple conflicting objectives. The ...

In this research, the lateral buckling analysis and layup optimization of the laminated composite of web and flanges tapered ... sequences are obtained using the non-dominated sorting genetic ...

Among them, safety, punctuality, energy saving and other performance are particularly worthy of attention. Therefore, the research on the multi-objective optimization of trains can not only ensure the ...