This paper deals with the two-dimensional strip packing problem (2D-SPP) with the order/or multi-drop and vertical stability constraints. The existing exact algorithm that solves this problem is not ...

Every organism you have ever seen, every ecosystem you have ever walked through, is the ongoing output of an algorithm that ...

Throughout history, most of the world’s genomic research has relied on Ananyo Choudhury from people of European ancestry. A ...

As predictive medicine advances, legal scholars warn that decades-old federal guidelines could set up a potential clash between your genes and your job.

Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...

MicroAlgo Inc. (the 'Company' or 'MicroAlgo') (NASDAQ: MLGO), today announced the proposal of a powerful solution-a multi-objective evolutionary search strategy, which is an innovative automated tool ...

Genetic algorithms (GAs) are a class of population-based metaheuristic search methods inspired by principles of natural selection and evolution. They solve complex optimisation problems by encoding ...

Abstract: This paper contains a comparison between a Genetic Algorithm (GA) and a Non-dominated Sorting Genetic Algorithm II (NSGA-II) on the Portfolio Optimisation Problem, based on the Modern ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

The original version of this story appeared in Quanta Magazine. For computer scientists, solving problems is a bit like mountaineering. First they must choose a problem to solve—akin to identifying a ...

Abstract: The genetic algorithm is one of the most commonly used metaheuristics due to its adaptability to various types of problems. However, its implementation can be challenging because of the ...