In other words, if conventional AI thinks, embodied AI both thinks and moves. That shift is central to the next phase of Industry 4.0: It changes how factories are designed, how supply chains operate ...

Every enterprise leader has seen the pattern: a proof-of-concept AI tool that impresses in the demo and then three months later, it's hemorrhaging accuracy, choking on edge cases, and nobody can ...

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 ...

For the past two years, we’ve been living in AI’s gold rush era. To borrow from Taylor Swift, think of it as the “Lover” phase where everything is shiny, new, and full of possibility. But we’re ...

We present OPT-BENCH, a benchmark comprising 20 machine learning tasks and 10 NP problems, specifically designed to assess large language models’ (LLMs) ability to solve problems with large search ...

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 ...

Abstract: Many engineering design optimization problems can be represented as mixed-variable optimization problems. This study presents a heuristic approach for solving mixed-variable optimization ...

Abstract: A wide range of real applications can be modelled as the multiobjective traveling salesman problem (MOTSP), one of typical combinatorial optimization problems. Meta-heuristics can be used to ...

1 School of Mathematics and Statistics, Fuzhou University, Fuzhou, China. 2 College of Computer and Data Science, Fuzhou University, Fuzhou, China. In this paper, we use Physics-Informed Neural ...

1 Department of Mathematics, University of Ndjamena, Ndjamena, Tchad. 2 Department of Mathematics and Computer Science, University of Cheikh. A. Diop, Dakar, Senegal. In the evolving landscape of ...