For power engineers, Python has become the default glue language for automation, data analysis, and algorithm development. In the meantime, QSPICE has emerged as a high-performance SPICE-class ...

Combinatorial optimization and integer programming form the backbone of decision-making models in which discrete choices must be made under constraints. At its core, integer programming specialises in ...

Global optimization of nonlinear mixed-integer programming (MINLP) addresses decision problems in which some variables are constrained to take integer values, while the objective function or ...

In “The Mixed Marriage Project,” Dorothy Roberts reflects on her anthropologist father’s lifelong project: to document — and promote — interracial marriages like his own. By Julia Scheeres Julia ...

ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...

(RTTNews) - Integer Holdings Corporation (ITGR) dropped 33.64% to trade at $72.40, down $36.71, after reporting the third quarter 2025 results showing revenue of $467.7 million, a +8% YoY, and ...

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...

Working with numbers stored as strings is a common task in Python programming. Whether you’re parsing user input, reading data from a file, or working with APIs, you’ll often need to transform numeric ...

Meta AI has released Llama Prompt Ops, a Python package designed to streamline the process of adapting prompts for Llama models. This open-source tool is built to help developers and researchers ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

Abstract: Machine Learning (ML)-based optimization frameworks emerge as a promising technique for solving large-scale Mixed Integer Linear Programs (MILPs), as they can capture the mapping between ...