NVIDIA's GPU-accelerated cuOpt engine discovers new solutions for four MIPLIB benchmark problems, outperforming CPU solvers with 22% lower objective gaps. NVIDIA's cuOpt optimization engine has found ...

Optimization problems often involve situations in which the user's goal is to minimize and/or maximize not a single objective function, but several, usually conflicting, functions simultaneously. Such ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

Microbial communities are able to carry out myriad functions of biotechnological interest, ranging from the degradation of industrial waste to the synthesis of valuable chemical products. Over the ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new algorithm appears to do it for some critical optimization tasks. For ...

Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...

ENFORCpp is a C++ tool that allows you to solve nonlinear constrained optimization problems. The tool is designed with real-time considerations and is suitable for online trajectory and control input ...

Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States ...

Abstract: This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the ...