# Francisco J. RodríguezUniversidad de Burgos | UBU · Computer Science

Francisco J. Rodríguez

## About

34

Publications

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658

Citations

Citations since 2017

## Publications

Publications (34)

Reconstructing complex network structures from measurable data has become a central issue in contemporary network science and engineering. In this paper, we tackle the reconstruction of the network topology from a set of target betweenness centrality values. This metric evaluates the participation of the vertices in the communication along the shor...

In any sport the selection of players for a team is fundamental for its subsequent performance. Many factors condition the selection process from the characteristics of the sport discipline to financial limitations, including a long list of restrictions associated with the environment of the competitions in which the team takes part. All of this ma...

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutio...

Energy awareness has gained momentum over the last decade in the software industry, as well as in environmentally concious society. Thus, algorithm designers and programmers are paying increasing attention this issue, particularly when handheld devices are considered, given their battery-consuming characteristics. When we focus on Evolutionary Algo...

Article whose content could help reduce the spread of CoVid-19 disease // Network theory and its applications arise in a variety of scientific fields (such as physics, engineering, sociology, psychology, criminology, epidemiology, biology, and many others), due to the inherent network’s ability to logically represent important relationships (edges)...

When a music student begins training, one of the main problems encountered is the proper understanding of
specific terms that teachers introduce as a way of analyzing the type of sound produced by the student. The
goal of a music teacher is that their students improve the quality of the sound they are emitting, but not in all
cases students underst...

Currently much of the pre-harvest fruit valuation is still done by farmers or technicians that visually inspect the pieces of fruit. However, this process has great limitations since their decisions have high subjectivity and a thorough analysis of the whole production, or even a significant part of it, is unapproachable. Therefore, computer vision...

Over the past few years, the task of conceiving effective attacks to complex
networks has arisen as an optimization problem. Attacks are modelled as the
process of removing a number k of vertices, from the graph that represents
the network, and the goal is to maximise or minimise the value of a predefined
metric over the graph. In this work, we pre...

En los últimos años, ha crecido el interés en formular como un problema de optimización la tarea de concebir ataques efectivos que causen el máximo daño sobre redes complejas. En este caso, los ataques se modelan como un proceso de eliminación de k vértices del grafo que representa la red. En este trabajo, seguimos esta línea de investigación prese...

Este trabajo está enfocado a la distinción y análisis de diferentes variedades de ciruelas utilizando técnicas de tratamiento de imágenes y minería de datos. En concreto, se analizan cuatro conjuntos de datos en los que se presentan tres variedades de ciruela en fase de maduración temprana: Black Splendor, OwenT y Angelino. La principal dificultad...

En este reporte técnico presentamos un software de ayuda a la decisión capaz de determinar estrategias eficientes para el desmantelamiento de redes terroristas. Su finalidad es ser útil a las fuerzas de seguridad para actuar de forma precisa e inminente en situaciones de respuesta frente a estas peligrosas redes delictivas. Para desarrollar el soft...

Given a set of positive integers S, the minimum generating set problem consists in finding a set of positive integers T with a minimum cardinality such that every element of S can be expressed as the sum of a subset of elements in T. It constitutes a natural problem in combinatorial number theory and is related to some real-world problems, such as...

In this paper, we propose a randomized greedy multi-start algorithm for the minimum common integer partition problem. Given k multisets of positive integers ( ), the goal is to find the common integer partition T with minimal cardinality, i.e., a unique and reduced multiset T that, for each Si, it can be partitioned into mi multisets Tj so that the...

The firefighter problem is a deterministic discrete-time model for the spread and containment of fire on a graph. Once the fire breaks out at a set of vertices, the goal addressed in this work is to save as many vertices as possible from burning. Although the problem finds applications in various real-world problems, such as the spread of diseases...

In this work, we propose a novel constructive method to deal with the unweighted minimum string cover problem. Given a set of strings S, this defiant optimization problem aims to find a minimum set of substrings M from S such that every string in S can be written as a concatenation of the strings in M. This problem has challenging real-world applic...

This chapter presents the fundamental concepts of genetic algorithms (GAs) that have become an essential tool for solving optimization problems in a wide variety of fields. The first part of this chapter is devoted to the revision of the basic components for the design of GAs. We illustrate this construction process through its application for solv...

Multi-document summarization has been used for extracting the most relevant sentences from a set of documents, allowing the user to more quickly address the content thereof. This paper addresses the generation of extractive summaries from multiple documents as a binary optimization problem and proposes a method, based on CHC evolutionary algorithm...

The quadratic multiple knapsack problem (QMKP) consists in assigning a set of objects, which interact through paired profit values, exclusively to different capacity-constrained knapsacks with the aim of maximising total profit. Its many applications include the assignment of workmen to different tasks when their ability to cooperate may affect the...

The firefigther problem is a deterministic discrete-time model for the spread (and the containment) of fire on an undirected graph. Assuming that the fire breaks out at a predefined set of vertices, the goal is to save as many vertices as possible from burning. The same model has also been used in the literature for the simulation of the spreading...

The quadratic minimum spanning tree problem consists of determining a spanning tree that minimizes the sum of costs of the edges and pairs of edges in the tree. Many algorithms and methods have been proposed for this hard combinatorial problem, including several highly sophisticated metaheuristics. This article presents a simple Tabu Search (TS) fo...

Iterated greedy search is a simple and effective metaheuristic for combinatorial problems. Its flexibility enables the incorporation of components from other metaheuristics with the aim of obtaining effective and powerful hybrid approaches. We propose a tabu-enhanced destruction mechanism for iterated greedy search that records the last removed obj...

In this work, we tackle the problem of scheduling a set of jobs on a set of unrelated parallel machines with minimising the total weighted completion times as performance criteria. The iterated greedy metaheuristic generates a sequence of solutions by iterating over a constructive heuristic using destruction and construction phases. In the last few...

In this paper, an artificial bee colony algorithm is proposed to solve the maximally diverse grouping problem. This complex optimisation problem consists of forming maximally diverse groups with restricted sizes from a given set of elements. The artificial bee colony algorithm is a new swarm intelligence technique based on the intelligent foraging...

In this work, we tackle the problem of scheduling a set of jobs on a set of non-identical parallel machines with the goal of minimising the total weighted completion times. GRASP is a multi-start method that consists of two phases: a solution construction phase, which randomly constructs a greedy solution, and an improvement phase, which uses that...

The design of hybrid metaheuristics with ideas taken from the simulated annealing and evolutionary algorithms fields is a fruitful research line. In this paper, we first present an overview of the hybrid metaheuristics based on simulated annealing and evolutionary algorithms presented in the literature and classify them according to two well-known...

No free lunch theorems for optimisation suggest that empirical studies on benchmarking problems are pointless, or even cast negative doubts, when algorithms are being applied to other problems not clearly related to the previous ones. Roughly speaking, reported empirical results are not just the result of algorithms’ performances, but the benchmark...

In this work, we tackle the problem of scheduling a set of jobs on a set of non-identical parallel machines with the goal of minimising the total weighted completion times. Artificial bee colony (ABC) algorithm is a new optimization technique inspired by the intelligent foraging behaviour of honey-bee swarm. These algorithms have shown a better or...

The problem of allocating a set of facilities in order to maximise the sum of the demands of the covered clients is known as the maximal covering location problem. In this work we tackle this problem by means of iterated greedy algorithms. These algorithms iteratively refine a solution by partial destruction and reconstruction, using a greedy const...

The flexible architecture of evolutionary algorithms allows specialised models to be obtained with the aim of performing as other search methods do, but more satisfactorily. In fact, there exist several evolutionary proposals in the literature that play the role of local search methods. In this paper, we make a step forward presenting a specialised...

Differential Evolution is a simple yet powerful algorithm for continuous optimisation problems. Traditionally, its operators combine the information
of randomly chosen vectors of the population. However, four different roles are clearly identified from their formulations:
receiving, placing, leading, and correcting vectors. In this work, we propose...

No Free Lunch theorems for optimisation state that there does not exist any algorithm better than any other one when averaged performances over the whole set of possible problems are considered. However, it has been recently suggested that algorithms might show performance differences when just the set of real-world problems is under study. In this...

The design of hybrid metaheuristics with ideas from the simulated annealing and evolutionary algorithms fields is a fruitful research line. In this paper, we present a new hybrid algorithm based on a genetic algorithm, whose search process simulates several parallel simulated annealing processes. An empirical study comparing the new model with clas...