Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

Graduate Program in Biotechnology, Federal University of Pará, Belém 66075-110, Brazil Graduate Program in Process Engineering, Federal University of Pará, Belém 66075-110, Brazil Faculty of Chemical ...

1 Department of Mathematics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh. 2 Department of Mathematics, Uttara University, Dhaka, Bangladesh. This study presents a ...

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 ...

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 ...

In today’s fast-paced, ever-evolving world, the complexity of challenges faced in both business and everyday life requires a shift in how we approach problem solving. Traditional linear thinking, ...

Annealing processors (APs) are gaining popularity for solving complex optimization problems. Fully-coupled Ising model APs are especially valued for their flexibility, but balancing capacity (number ...

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 ...

Abstract: Conjugate gradient techniques are widely used to solve unconstrained optimization issues. The accelerated conjugate gradient approach provides superior numerical effects for the ...