Researchers have developed a new algorithmic model that can improve predictions of cooling demand for greener buildings. This ...

Research team debuts the first deterministic streaming algorithms for non-monotone submodular maximization, delivering superior approximation ratios with minimal memory and real-time throughput on ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine ...

Fruchter, G. (2026) Opportunism in Supply Chain Recommendations: A Dynamic Optimization Approach. Modern Economy, 17, 26-38.

FAYETTEVILLE, GA, UNITED STATES, December 31, 2025 /EINPresswire.com/ — Artificial intelligence (AI) is increasingly transforming computational mechanics, yet many AI-driven models remain limited by ...

SLSQP stands for Sequential Least Squares Programming. It is a numerical optimization algorithm used to solve constrained nonlinear optimization problems. In this project, we aim to optimize objective ...

This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...

Abstract: The utilization of both constrained and unconstrained-based optimization for solving constrained multiobjective optimization problems (CMOPs) has become prevalent among recently proposed ...

The immigration bill being used by vulnerable Democrats as evidence of their commitment to border security has been trashed by Republican senators, who claim the measure would have actually ...

Abstract: An optimization problem is the problem of finding the best solution from all feasible solutions. Solving optimization problems can be performed by heuristic algorithms or classical ...