Antonio Bolufé-Röhler

Antonio Bolufé-Röhler
University of Prince Edward Island | UPEI · Computer Science

PhD and MS in Mathematics, BSc in Computer Science

About

53
Publications
145,335
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539
Citations
Introduction
Antonio Bolufé-Röhler is Assistant Profesor at the University of Prince Edward Island. Antonio does research in Optimization, Artificial Intelligence, Statistics, Machine Learning and Applied Mathematics. Currently his main research project is 'Towards Exploration-only, Exploitation-only Hybrid Search Techniques.'
Additional affiliations
July 2018 - present
University of Prince Edward Island
Position
  • Professor (Assistant)
September 2014 - present
University of Havana
Position
  • Head of Department
September 2007 - present
University of Havana
Position
  • Lecturer

Publications

Publications (53)
Conference Paper
Full-text available
During the search process of differential evolution (DE), each new solution may represent a new more promising region of the search space (exploration) or a better solution within the current region (exploitation). This concurrent exploitation can interfere with exploration since the identification of a new more promising region depends on finding...
Conference Paper
Full-text available
Matheuristics are heuristic algorithms made by the interoperation of metaheuristics and mathematic programming (MP) techniques. An essential feature is the exploitation in some part of the algorithms of features derived from the mathematical model of the problems of interest, thus the definition “model-based metaheuristics” appearing in the title o...
Article
Full-text available
The existence of the curse of dimensionality is well known, and its general effects are well acknowledged. However, and perhaps due to this colloquial understanding, specific measurements on the curse of dimensionality and its effects are not as extensive. In continuous domains, the volume of the search space grows exponentially with dimensionality...
Article
Full-text available
Recent research has consistently shown that the concurrence between exploration and exploitation can significantly limit the effectiveness of exploration on heuristic search. This has led to the design of hybrid algorithms that separate both task and alleviate this limitation. Many of these hybrids are based on the Leaders and Followers metaheurist...
Article
Full-text available
It is difficult to segment Glioma and its internal structure because the Glioma boundaries have edemas and complex internal structures. This paper proposes a new optimized, integrated 3D U-Net network to achieve accurate segmentation of Glioma and internal subareas. The contribution of this paper is twofold, it studies the clinical path of patients...
Article
LAY SUMMARY This research explored the demographic, military service, and health characteristics associated with cannabis for medical purposes (CMP) reimbursements among Veterans Affairs Canada (VAC) clients and respondents of the Life After Service Survey 2016 (LASS). Of the initial number of indicators selected contained in LASS 2016 survey, some...
Technical Report
Full-text available
The report presents the best S-boxes found with Leaders and Followers hybrids.
Article
Full-text available
Minimum Population Search is a recently developed metaheuristic for optimization of mono-objective continuous problems, which has proven to be a very effective optimizing large scale and multi-modal problems. One of its key characteristic is the ability to perform an efficient exploration of large dimensional spaces. We assume that this feature may...
Conference Paper
Full-text available
The goal of exploration to produce diverse search points throughout the search space can be countered by the goal of selection to focus search around the fittest current solution(s). In the limit, if all exploratory search points are rejected by selection, then the behaviour of the metaheuristic will be equivalent to one which performs no exploratio...
Conference Paper
Exploration and exploitation are analyzed in Particle Swarm Optimization (PSO) through a set of experiments that make new measurements of these key features. Compared to analyses on diversity and particle trajectories, which focus on particle motions and their potential to achieve exploration and exploitation, our analysis also focuses on the pbest...
Conference Paper
S-boxes are used to provide confusion in symmetric-key cryptography, thus finding S-boxes with good properties is fundamental to ensure the resistance against diverse cryptanalyses. Specifically, finding balanced S-boxes with high nonlinearity and low transparency order is a NP-hard problem. The transparency order is an important property since it...
Code
Linear equilibrium constrained programming is a special class of optimization models with equilibrium constraints. Because of the complexity of the equilibrium condition it is replaced by necessary conditions, which leads to a complementarity constrained problem (MPCC). The set of feasible solutions in a MPCC is structured as a union of polyhedrons...
Article
Full-text available
Spanish abstract Los problemas lineales con restricciones de equilibrio son un caso particular de los modelos de optimización con restricciones de equilibrio. Debido a la complejidad que presentan, la condición de equilibrio se sustituye por condiciones necesarias obteniéndose un problema con restricciones de complementariedad (MPCC). La estructura...
Conference Paper
Full-text available
Los Algoritmos de Estimación de Distribución corren el riesgo de converger prematuramente al perder diversidad en su población. La técnica de Thresheld Convergence ha sido exitosamente utilizada para superar esta dificultad en otras metaheurísticas. El presente trabajo aplica esta novedosa técnica al Algoritmo de Estimación Normal Multivariada, la...
Research
Full-text available
A primera vista puede parecer, y muchos estudiantes piensan así, que la filosofía y la computación poco tiene en común. Sin embargo, nada más alejado de la realidad. Diversos problemas científicos y técnicos abordados por la ciencia de la computación tienen importantes repercusiones filosóficas. Relevantes filósofos han aportado a la computación, y...
Thesis
Full-text available
With increasing dimensionality the performance of most optimization algorithms rapidly deteriorates. There are two major reasons for this decrease in performance: an increase of the landscape complexity and an exponential increase of the search space volume. Due to the first reason, unimodal functions may become multimodal in large dimensions. Due...
Conference Paper
Full-text available
Large-scale global optimization is a challenging task which is embedded in many scientific and engineering applications. Among large scale problems, multimodal functions present an exceptional challenge because of the need to promote exploration. In this paper we present a hybrid heuristic specifically designed for optimizing large scale multimodal...
Conference Paper
Full-text available
When optimizing multi-modal spaces, effective search techniques must carefully balance two conflicting tasks: exploration and exploitation. The first refers to the process of identifying promising areas in the search space. The second refers to the process of actually finding the local optima in these areas. This balance becomes increasingly import...
Article
Full-text available
A multi-modal search space can be defined as having multiple attraction basins – each basin has a single local optimum which is reached from all points in that basin when greedy local search is used. Optimization in multi-modal search spaces can then be viewed as a two-phase process. The first phase is exploration in which the most promising attrac...
Data
C-code implementation of Minimum Population Search for the CEC-2013 benchmark.
Article
Full-text available
Minimum Population Search is a new metaheuristic specifically designed for optimization of multi-modal problems. Its core idea is to guarantee full coverage of the search space with the smallest possible population. A small population increases the chances of convergence and the efficient use of function evaluations, but it can also induce the risk...
Conference Paper
Full-text available
The existence of the curse of dimensionality is well known, and its general effects are well acknowledged. However, perhaps due to this colloquial understanding, specific measurements on the curse of dimensionality and its effects are not as extensive. In continuous domains, the volume of the search space grows exponentially with dimensionality. Co...
Conference Paper
Full-text available
Minimum Population Search is a new metaheuristic specifically designed for optimizing multi-modal problems. Its core idea is to guarantee exploration in all dimensions of the search space with the smallest possible population. A small population increases the chances of convergence and the efficient use of function evaluations – an important consid...
Article
Full-text available
Computer modeling of protein-ligand interactions is one of the most important phases in a drug design process. Part of the process involves the optimization of highly multi-modal objective (scoring) functions. This research presents the Minimum Population Search heuristic as an alternative for solving these global unconstrained optimization problem...
Technical Report
Full-text available
Results for an implementation of Minimum Population Search on the CEC2013 Real-Parameter Optimization Benchmark Functions. Source codes: https://www.researchgate.net/publication/262318460_Minimum_Population_Search_%28MATLAB_code%29?ev=prf_pub https://www.researchgate.net/publication/274567146_MPS_for_CEC2013_%28C_code%29?ev=prf_pub
Technical Report
Full-text available
Results for an implementation of the Univariate Marginal Distribution Algorithm on the CEC2013 Real-Parameter Optimization Benchmark Functions
Article
Full-text available
Simulation and optimization of traffic flows in a city or province allow the implementation of correct developing strategies and help the decision making process when using and distributing resources such as mass transit. This estimation can be modeled as a bifurcated multi-commodity network flow problem, where the general flow distribution is dict...
Article
Full-text available
Simulation and optimization of traffic flows in a city or province allow the implementation of correct developing strategies and help the decision making process when using and distributing resources such as mass transit. This estimation can be modeled as a bifurcated multi-commodity network flow problem, where the general flow distribution is dict...
Article
Full-text available
Simulation and optimization of traffic flows in a city or province allow the implementation of correct developing strategies and help the decision making process when using and distributing resources such as mass transit. This estimation can be modeled as a bifurcated multi-commodity network flow problem, where the general flow distribution is dict...
Technical Report
Full-text available
Results for an implementation of Standard Particle Swarm Optimization on the CEC2013 Real-Parameter Optimization Benchmark Functions This revised version is based on fixing a code error in the previous version. See the Appendix for more details. Source code: https://www.researchgate.net/publication/259643342_Source_code_for_an_implementation_of_S...
Article
Full-text available
El cómputo de alto rendimiento es una necesidad para el desarrollo de investigaciones con grandes volúmenes de datos. La creciente demanda de este tipo de resultados ha impulsado a varios centros de investigación a poner en funcionamiento recursos de cómputo de alto rendimiento. En Cuba no existe una solución definitiva que permita a todos los cent...
Conference Paper
Full-text available
El Two Dimensional Strip Packing(2SP) es un complejo y bien conocido problema de optimización NP-duro con una gran aplicación práctica en diferentes industrias. El problema consiste en empaquetar un conjunto de piezas rectangulares en una cinta tal que se minimice la altura del empaquetado. Diversos algoritmos pueden consultarse en la literatura pa...
Conference Paper
Full-text available
Population-based heuristics can be effective at optimizing difficult multi-modal problems. However, population size has to be selected correctly to achieve the best results. Searching with a smaller population increases the chances of convergence and the efficient use of function evaluations, but it also induces the risk of premature convergence. L...
Conference Paper
Full-text available
The simulation and optimization of traffic flows in a city or province allow the implementation of correct developing strategies and help the decision making process when using and distributing resources such as mass transit. This estimation can be modeled as a bifurcated multi-commodity network flow problem, where the general flow distribution is...
Conference Paper
Full-text available
El Two Dimensional Strip Packing (2SP) es un complejo y bien conocido problema de optimización NP-duro con una gran aplicación práctica en diferentes industrias. El problema consiste en empaquetar un conjunto de piezas rectangulares en una cinta tal que se minimice la altura del empaquetado. Dada la considerable complejidad computacional de este pr...
Conference Paper
Full-text available
Multi-swarm systems base their search on multiple sub-swarms instead of one standard swarm. The use of diverse sub-swarms increases performance when optimizing multi-modal functions. However, new design decisions arise when implementing multi-swarm systems such as how to select the initial positions and initial velocities, and how to coordinate the...
Article
Full-text available
Recognizing the detrimental impact of information overload on user participation, in this paper we design and evaluate several algorithms to filter and rank the information on Social Networking Sites (SNS). As a first step we identify the factors that impact user evaluations of information shared through these networks in a set of regression analys...
Conference Paper
Full-text available
Particle swarm optimization cannot guarantee convergence to the global optimum on multi-modal functions, so multiple swarms can be useful. One means to coordinate these swarms is to use a separate search mechanism to identify different regions of the solution space for each swarm to explore. The expectation is that these independent sub-swarms can...
Thesis
Full-text available
La simulación y optimización de los flujos de tráfico en una ciudad o provincia permite la implementación de buenas estrategias de desarrollo a la vez que ayuda en el proceso de toma de decisiones cuando se controlan y distribuyen algunos recursos claves como el transporte masivo. La distribución de tráfico puede ser modelada como un problema de Fl...
Article
Full-text available
Matheuristic algorithms have begun to demonstrate that they can be the state of the art for some optimization problems. This paper puts forth that they can represent a viable option also in an applicative context. The possibility to get a solution quality vali-dation or a model grounded construction may become a significant competitive advantage ag...
Conference Paper
Full-text available
Soft variable fixing has emerged as one of the main techniques that the area of matheuristics can contribute to general metaheuristics. Recent years have in fact witnessed a fruitful interplay of methods that were originally proposed as general metaheuristcs with methods rooted in mathematic programming, which can be applied alone or as hybrids for...
Chapter
Soft variable fixing has emerged as one of the main techniques that the area of matheuristics can contribute to general metaheuristics. Recent years have in fact witnessed a fruitful interplay of methods that were originally proposed as general metaheuristcs with methods rooted in mathematic programming, which can be applied alone or as hybrids for...

Questions

Questions (19)
Question
In recent year most advances in the field of Artificial Intelligence have come from the neural network community, what other relevant breakthrough have been achieved in the last two decades?
Question
(Meta)Heuristic search algorithms gather a lot of sampling information as the search process proceeds. Can this information be used by machine learning algorithms to guide the search? For instance, to determine which search strategy is more effective or how to balance exploration and exploitation.
Question
I´m looking for examples of heuristic and metaheuristic algorithms applied to cryptographic problems.
Question
Which textbook would you recommend for lecturing a course in Artificial Intelligence?And which topics do you consider more relevant?

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Projects

Projects (3)
Project
A recurring research theme in metaheuristics is to consider the balance between Exploration and Exploitation. An often forgotten area of research is the balance between Selection and Exploration. It is noted that Selection has the ability to turn any exploratory search process into a hill climber by rejecting all exploratory search solutions. Recent experiments show that this occurs in Particle Swarm Optimization where the rejection of all exploratory particle positions can cause the swarm to stall before it can converge. The first goal of this workshop will be to reanalyze current metaheuristics from the perspective of selection (as opposed to exploration and/or an underlying metaphor). Subsequent results/goals include a selection-based taxonomy for the explosion of metaphor-based metaheuristics, tools to accurately measure exploration and the effects of selection on exploratory search solutions, the identification and categorization of selection errors, and suggestions for future methods of selection and metaheuristic design.
Project
Our research on thresheld convergence has shown how concurrent exploration and exploitation can interfere with subsequent exploration. We are currently developing techniques for exploration only, and these techniques subsequently need another technique for exploitation. We are combining these techniques in a new hybrid model that starts with an initial phase of exploration only before a distinct transition to a phased of exploitation only.
Project
Algorithm Minimum Population Search multi-objective approach.