Solving real-world optimization tasks using physics-informed neural computing
Abstract Optimization tasks are essential in modern engineering fields such as chip design, spacecraft trajectory determination, and reactor scenario development.Recently, machine learning applications, including deep reinforcement learning (RL) and genetic algorithms (GA), have emerged in these real-world optimization tasks.We introduce a new mach