The utilization of both constrained and unconstrained-based optimization for solving constrained multi-objective optimization problems (CMOPs) has become prevalent among recently proposed constrained ...

Many real-world dynamic problems have constraints, and in certain cases not only the objective function changes over time, but also the constraints. However, there is no research in answering the ...

UNIFY: a Unified Policy Designing Framework for Solving Constrained Optimization Problems with Machine Learning, Paper, Not Find Code (Arxiv, 2022) Enforcing Hard Constraints with Soft Barriers: Safe ...

Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.