If you have used our code for research purposes, please cite the publications mentioned above. For the sake of simplicity, we provide the Bibtex format: @article{Lapucci2024, author={Lapucci, Matteo ...

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 ...

Abstract: Knowledge transfer-based evolutionary optimization has garnered significant attention, such as in multitask evolutionary optimization (MTEO), which aims to solve complex problems by ...

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 ...

We walk through an optimization problem step by step, clearly explaining how to identify variables, set up the correct function, apply derivatives, and find maximum or minimum values. Each step is ...

A general-purpose Model Context Protocol (MCP) server for solving combinatorial optimization problems with logical and numerical constraints. This server provides a unified interface to multiple ...

A line of engineering research seeks to develop computers that can tackle a class of challenges called combinatorial optimization problems. These are common in real-world applications such as ...

Interval-valued optimization problems constitute a rapidly evolving field in applied mathematics and engineering, addressing situations where uncertainty and imprecision are inherent in model ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

Palo Alto, California-based D-Wave Quantum Inc. claims to be the first company that sells computers that leverage quantum effects in their operation. The company recently demonstrated how its quantum ...