Abstract: This paper discusses formulations and algorithms which allow a number of agents to collectively solve problems involving both (non-convex) minimization and (concave) maximization operations.

SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...

Performance Max has evolved dramatically since its 2021 launch. If you’re still running campaigns like it’s 2023, you’re leaving serious performance gains behind. With Google rolling out enhanced ...

Google Ads is introducing new user interface (UI)-only image optimization features, spotted last week, aimed at enhancing Performance Max campaigns, marking a shift in how advertisers can manage ...

Meta AI has released Llama Prompt Ops, a Python package designed to streamline the process of adapting prompts for Llama models. This open-source tool is built to help developers and researchers ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

You make decisions every day. Some are big, and some are small. But even the small decisions involve a great deal of complexity. Let me show you what I mean. Take something you probably do regularly: ...

Designing computational workflows for AI applications, such as chatbots and coding assistants, is complex due to the need to manage numerous heterogeneous parameters, such as prompts and ML ...

Vehicle Routing Problem with Backhaul (VRPB); Open vehicle routing problem; Lagrangian decomposition; Lagrangian relaxation algorithm; Clustering algorithm; CPLEX optimization solver; Python ...