Algorithms, Volume 16, Issue 4

A warehouse delivery problem consists of a set of robots that undertake delivery jobs within a warehouse. Items are moved around the warehouse in response to events. A solution to a warehouse delivery problem is a collision-free schedule of robot mov...

In this paper, we develop a novel hybrid recommender system for the tourism domain, which combines (a) a Bayesian preferences elicitation component which operates by asking the user to rate generic images (corresponding to generic types of POIs) in o...

Combinatorial clustering based on the Ising model is drawing attention as a high-quality clustering method. However, conventional Ising-based clustering methods using the Euclidean distance cannot handle irregular data. To overcome this problem,...

We explore several aspects of replica synchronization with the goal of retrieving the values of parameters applied to the Lorenz system. The idea is to establish a computer replica (slave) of a natural system (master, simulated in this paper), and ex...

As in manufacturing with its Industry 4.0 transformation, the enormous potential of artificial intelligence (AI) is also being recognized in the construction industry. Specifically, the equipment-intensive construction industry can benefit from using...

Digital transformation is a phenomenon introduced by the transformative power of digital technologies, and it has become a key driver for the energy sector, with advancements in technology leading to significant changes in the way energy is produced,...

Structural equation models (SEM) are widely used in the social sciences. They model the relationships between latent variables in structural models, while defining the latent variables by observed variables in measurement models. Frequently, it is of...

The field of application of data-driven product development is diverse and ranges from requirements through the early phases to the detailed design of the product. The goal is to consistently analyze data to support and improve individual steps in th...

Brain storm optimization (BSO) and particle swarm optimization (PSO) are two popular nature-inspired optimization algorithms, with BSO being the more recently developed one. It has been observed that BSO has an advantage over PSO regarding exploratio...

This paper considers the single-machine problem with job release times and flexible preventive maintenance activities to minimize total weighted tardiness, a complicated scheduling problem for which many algorithms have been proposed in the literatur...

We present a machine learning approach for applying (multiple) temporal aggregation in time series forecasting settings. The method utilizes a classification model that can be used to either select the most appropriate temporal aggregation level for...

Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data...

This work presents the application of a novel evolutional algorithmic approach to determine and reconstruct the specific 3-dimensional source location of gamma-ray emissions within the shelter object, the sarcophagus of reactor Unit 4 of the Chornoby...

Wireless sensor systems often fail to provide measurements with uniform time spacing. Measurements can be delayed or even miss completely. Resampling to uniform intervals is necessary to satisfy the requirements of subsequent signal processing. Commo...

Maintenance processes are of high importance for industrial plants. They have to be performed regularly and uninterruptedly. To assist maintenance personnel, industrial sensors monitored by distributed control systems observe and collect several mach...

Clipping algorithms essentially compute the intersection of the clipping object and the subject, so to go from two to three dimensions we replace the two-dimensional clipping object by the three-dimensional one (the view frustum). In three-dimensiona...

This paper focuses on antenna modeling using wire-grid and surface triangulation as two of the most commonly used MoM-based approaches in this field. A comprehensive overview is provided for each of them, including their history, applications, and li...

This work was greatly influenced by the opinions of one of the authors (JS), who demonstrated in a recent book that it is important to distinguish between “fractal models” and “fractal” (power-law) behaviors. According to the...

To solve the problem of text clustering according to semantic groups, we suggest using a model of a unified lexico-semantic bond between texts and a similarity matrix based on it. Using lexico-semantic analysis methods, we can create “term&ndas...

As an essential piece of infrastructure supporting cyberspace security technology verification, network weapons and equipment testing, attack defense confrontation drills, and network risk assessment, Cyber Range is exceptionally vulnerable to distri...

In this paper, we propose a method to aid authors in choosing alternative keywords that help their papers gain visibility. These alternative keywords must have a certain level of popularity in the scientific community and, simultaneously, be keywords...

Gaussian mixture modeling is a generative probabilistic model that assumes that the observed data are generated from a mixture of multiple Gaussian distributions. This mixture model provides a flexible approach to model complex distributions that may...

This paper presents NSGA-PINN, a multi-objective optimization framework for the effective training of physics-informed neural networks (PINNs). The proposed framework uses the non-dominated sorting genetic algorithm (NSGA-II) to enable traditional st...

In this paper, we study the flow of signals through linear paths with the nonlinear condition that a node emits a signal when it receives external stimuli or when two incoming signals from other nodes arrive coincidentally with a combined amplitude a...

As a practical application of Optical Character Recognition (OCR) for the digital situation, the digital instrument recognition is significant to achieve automatic information management in real-industrial scenarios. However, different from the norma...

The simulation-based design optimization (SBDO) paradigm is a well-known approach that has assisted, assists, and will continue to assist designers to develop ever-improving systems [...]

Skeleton-based action recognition depends on skeleton sequences to detect categories of human actions. In skeleton-based action recognition, the recognition of action scenes with more than one subject is named as interaction recognition. Different fr...

The identification of fault locations (FL) on overhead power lines (OHPLs) in the shortest possible time allows for a reduction in the time to shut down OHPLs in case of damage. This helps to improve the reliability of power systems. FL devices on OH...

This is a Special Issue of the open-access journal Algorithms consisting of surveys in theoretical computer science [...]

Nonnegative matrix factorization can be used to automatically detect topics within a corpus in an unsupervised fashion. The technique amounts to an approximation of a nonnegative matrix as the product of two nonnegative matrices of lower rank. In cer...

In many tasks related to an object’s observation or real-time monitoring, the gathering of temporal multimodal data is required. Such data sets are semantically connected as they reflect different aspects of the same object. However, data sets...

Over the last decades, the development of Answer Set Programming (ASP) has brought about an expressive modeling language powered by highly performant systems. At the same time, it gets more and more difficult to provide semantic underpinnings capturi...

The time-dependent diffusion equation is studied, where the diffusion coefficient itself depends simultaneously on space and time. First, a family of novel, nontrivial analytical solutions is constructed in one space dimension with the classical self...

The complexity of products increases considerably, and key functions can often only be realized by using high-precision components. Microgears have a particularly complex geometry and thus the manufacturing requirements often reach technological limi...

Recommender systems aim to forecast users’ rank, interests, and preferences in specific products and recommend them to a user for purchase. Collaborative filtering is the most popular approach, where the user’s past purchase behavior cons...

A lack of transparency in machine learning models can limit their application. We show that analysis of variance (ANOVA) methods extract interpretable predictive models from them. This is possible because ANOVA decompositions represent multivariate f...

Synchronization of food chain models is an intensely investigated area in dynamical systems. Two pioneering models in three species food chain systems exhibiting chaotic dynamics are the Hastings and Powell (HP) model and the Upadhyay and Rai (UR) mo...

We address the problem of evolutionary system design (ESD) by means of answer set programming modulo difference constraints (AMT). The goal of this design approach is to synthesize new product variants or generations from existing products. We start...

Autoencoders have been used widely for diagnosing devices, for example, faults in rotating machinery. However, autoencoder-based approaches lack explainability for their results and can be hard to tune. In this article, we propose an explainable meth...

In recent years, energy prices have become increasingly volatile, making it more challenging to predict them accurately. This uncertain market trend behavior makes it harder for market participants, e.g., power plant dispatchers, to make reliable dec...

Creating machines that behave and work in a way similar to humans is the objective of artificial intelligence (AI). In addition to pattern recognition, planning, and problem-solving, computer activities with artificial intelligence include other acti...