This paper presents the Secant Optimization Algorithm (SOA), a novel mathematics-inspired metaheuristic derived from the Secant Method. SOA enhances search efficiency by repeating vector updates using ...

Solving complex engineering optimization problems can improve design quality, reduce costs, and enhance performance and reliability. However, these problems are often nonlinear, non-convex, and ...

We review encoding and hardware-independent formulations of optimization problems for quantum computing. Using this generalized approach, an extensive library of optimization problems from the ...

Understanding the current state of technology requires understanding its origins. This reading list provides sources relevant to the form of generative AI that led to natural language processing (NLP) ...

Open systems aren’t inherently less secure than their proprietary counterparts, and open source code is not inherently less secure than proprietary code. Instead, Open Source Software (OSS) poses ...

A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of ...

Thermodynamic laws fundamentally limit the efficiency and accuracy of living systems. To perform essential functions, from sensing to replication and locomotion, organisms consume energy and dissipate ...

Autoregressive Integrated Moving Average models are perfect for time series prediction Used it on data that includes a seasonal temporal shift. The data was non-stationary and had trends in the ...