Large-scale systems rely on heuristics to tackle NP-hard problems such as traffic engineering, virtual machine placement, and packet scheduling. While these heuristics are efficient, they can exhibit ...

Search has moved beyond blue links. In 2026, visibility is increasingly determined by whether AI systems select, summarize, and cite your brand inside generative answers. That shift is what makes ...

Driven by the artificial intelligence frenzy, Microsoft is internally projecting that water use at its data centers will more than double by 2030 from 2020, including in places that face shortages.

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Project status: retired experiment (not a real product). This was the paid-tier add-on to my finops-dbt Starter project, an experiment in what a "Pro" pack might look like on top of the open-source ...

Tractability of the introduced models and performance of the proposed constructive heuristics will be evaluated with the 50 large-sized instances proposed in [4], that were introduced for the FJS ...

Abstract: A powerful paradigm called cloud computing, which shares information across the Internet, quickly serves the demands of companies and individuals. A data replication approach for data nodes ...

Query optimisation in distributed database systems addresses the challenge of selecting an efficient execution plan across multiple networked nodes. Owing to the combinatorial explosion of possible ...

Abstract: In this study, we propose a novel approach to accelerate online mixed-integer optimization using heuristics, the interior point method, and an integrated clustering and sorting technique.