Cost Function Design: Needs to balance path length, safety, energy consumption, and dynamic feasibility (for instance, robotic arms need to avoid joint limits). Industrial case: An AGV (Automated ...

Recently, a research team from the Rudolf Technology Center in Slovenia proposed a new method to optimize the sparse subgraph problem, which has wide applications in fields such as network analysis ...

Abstract: This paper investigates the distributed convex optimization problem where dimension of the feasible set is fluctuated. To address this, we formulate an open consensus algorithm that enables ...

The constant scaling of AI applications and other digital technologies across industries is beginning to tax the energy grid due to its intensive energy consumption. Digital computing's energy and ...

Abstract: Nonconvexity is a usually overlooked factor in economic dispatch (ED). Enhancing the nonconvexity of the objective function leads traditional convex optimization algorithms easily to fall ...

SCE-UA is a lightweight Python package implementing the Shuffled Complex Evolution (SCE-UA) algorithm for global optimization. Designed primarily for hydrological model calibration, it leverages NumPy ...

The AI Prompt Optimization Platform is a professional tool designed to help users optimize prompts for AI models, enhancing AI conversation effectiveness and response accuracy. The platform integrates ...