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¿Es P igual a NP o es P distinto de NP? El dilema que acaba de leer admite la concesión o negación de cualquiera de sus dos premisas, y demostrar qué camino es el correcto está premiado con un millón de dólares po...

Subjects / keywords: Ingeniería y Tecnología; General

Abstract This study introduces two recently developed bio-inspired metaheuristic algorithms, Artificial Protozoa Optimizer (APO, 2024) and Dung Beetle Optimizer (DBO, 2023), into long short-term memory (LSTM) networks fo...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

Este texto plantea una primera aproximación a la Optimización Metaheurística en Ingeniería de Organización. Entendiendo como optimización metaheurística a un conjunto de procedimientos para resolver problemas comp...

Trata de la estimación de parámetros del proceso de cromatografía líquida de columna mediante técnicas basadas en algoritmos metaheurísticos.

Trata de un método para obtener predicados difusos a partir de datos utilizando metaheurísticas.

Subjects / keywords: Economía y Comercio; Economía; General

Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Bal...

Abstract The emergence of Internet-of-Things devices and expanding data processing demands have led to the popularization of edge computing. But energy efficiency challenges and security problems also remain difficult in...

BackgroundLast-mile logistics accounts for approximately 28% of total logistics costs and is a major contributor to urban carbon emissions. The integration of drones with electric trucks offers a path toward more efficie...

This study introduces Felis Catus Optimization (FCO), a novel nature‑inspired metaheuristic algorithm modeled on the ecological and adaptive behavioral dynamics of urban domestic cats. FCO divides its population into e...

The portfolio optimization problem is a mathematical and financial decision-making method that aims to achieve an optimal trade-off between financial risk and return. This paper presents the first application of the nove...

Wildfires are among the most destructive natural disasters and pose significant risks to ecosystems, infrastructure, and human lives. This study focuses on wildfire susceptibility mapping in Los Angeles County, a region ...

Las mal llamadas teorías del caos y de la complejidad, elaboradas en las dos últimas décadas del siglo XX y en lo que va del tercer milenio, han aportado numerosos elementos de juicio, elaboraciones algorítmicas y he...

Se propone una medida denominada calidad de la similaridad de un sistema de decisión; un método para construir relaciones de similaridad, a partir de la combinación de la metaheurística optimización basada en partí...

Operations Research, Management Science or Business Analytics is a technology that helps improve business decision making. This book is focused on linear, integer, nonlinear and multiobjective programming, as well as mul...

La inteligencia artificial es hoy la herramienta esencial para afrontar la explosión de datos, la interconexión global y la creciente complejidad de los sistemas modernos. Dentro de ella, la inteligencia computacional ...

The immense amount of data managed during the diagnosis process overwhelms, by far, the clinicians’ processing capabilities. Artificial intelligence methods like Multi-Layer Perceptrons come to help by providing a seco...

Discriminant Analysis can best be defined as a technique which allows the classification of an individual into several dictinctive populations on the basis of a set of measurements. Stepwise discriminant analysis (SDA) i...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...

Abstract The flexible job shop scheduling problem (FJSP) is considered as an important problem in the modern manufacturing system. It is known to be an NP-hard problem. Most of the algorithms used in solving FJSP problem...

Abstract This research employs hybrid machine learning techniques to optimize the mechanical properties of 3D-printed polylactic acid (PLA) lattice structures. By integrating random forest (RF) and XGBoost (XGB) algorith...

Abstract Timely and accurate detection of COVID-19 is essential for rapid intervention and preventing the spread of the disease, especially among vulnerable populations. This study introduces a new two-stage methodology ...