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Camino Vela

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University of Turku

Carnegie Mellon University

New York University

Yann Chevaleyre

Université Sorbonne Paris Nord / Sorbonne Paris Nord University

Sergey Muravyov

Tomsk Polytechnic University

Thierry Marchant

Ghent University

Jayant Kalagnanam

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Papers by Camino Vela

Runtime bounds prediction for the Kemeny problem

Journal of Ambient Intelligence and Humanized Computing

The time required for solving the ranking aggregation problem using the Kemeny method increases f... more The time required for solving the ranking aggregation problem using the Kemeny method increases factorially with the number of alternatives to be ranked, which prevents its use when this number is large. Exact algorithms use domain information to discard rankings as possible solution, thus saving runtime. The amount of rankings that can be discarded varies for each profile and cannot be known beforehand. For profiles of rankings with large number of alternatives, the amount of rankings discarded highly affects the feasibility of the computation of Kemeny ranking. How to identify the profiles that are more time-consuming when finding the Kemeny ranking is not trivial. In this work we propose the use of machine learning models to predict how difficult is to obtain the Kemeny ranking in terms of runtime. The results obtained are promising, with values of the area under the curve metric over 80%. Furthermore, it is possible to extract from the proposed models the characteristics of the ...

Reducing the Computational Time for the Kemeny Method by Exploiting Condorcet Properties

Mathematics, 2021

Preference aggregation and in particular ranking aggregation are mainly studied by the field of s... more Preference aggregation and in particular ranking aggregation are mainly studied by the field of social choice theory but extensively applied in a variety of contexts. Among the most prominent methods for ranking aggregation, the Kemeny method has been proved to be the only one that satisfies some desirable properties such as neutrality, consistency and the Condorcet condition at the same time. Unfortunately, the problem of finding a Kemeny ranking is NP-hard, which prevents practitioners from using it in real-life problems. The state of the art of exact algorithms for the computation of the Kemeny ranking experienced a major boost last year with the presentation of an algorithm that provides searching time guarantee up to 13 alternatives. In this work, we propose an enhanced version of this algorithm based on pruning the search space when some Condorcet properties hold. This enhanced version greatly improves the performance in terms of runtime consumption.

The Borda Count as an Initial Threshold for Kemeny Ranking Aggregation

Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP), 2021

The need of establishing a consensus ranking from the preferences expressed by different voters a... more The need of establishing a consensus ranking from the preferences expressed by different voters arises in several contexts. The method proposed by Kemeny to this purpose is famously known due to its numerous fulfilled properties and intuitive interpretation, as it minimizes the number of pairwise comparisons in which the consensus ranking disagrees with the preferences given by the voters. Nevertheless, this method has a main drawback regarding its execution time, thus preventing its use in practice. There exist some other methods, such as the Borda Count, that can be computed in polynomial time, even though they do not fulfill as many intuitive properties as the Kemeny method. Here, we propose to use the Borda Count ranking as the initial solution of a Branchand-Bound algorithm for reducing the execution time of the Kemeny method. The presented experiments show that this approach leads to an improvement in execution time.

Multi-objective evolutionary algorithm for solving energy-aware fuzzy job shop problems

Soft Computing, 2020

A growing concern about the environmental impact of manufacturing processes and in particular, th... more A growing concern about the environmental impact of manufacturing processes and in particular, the associated energy consumption, has recently driven some researchers within the scheduling community to consider energy costs in addition to more traditional performance-related measures, such as satisfaction of due-date commitments. Recent research is also devoted to narrowing the gap between real-world applications and academic problems by handling uncertainty in some input data. In this paper we address the job shop scheduling problem, a well-known hard problem with many applications, using fuzzy sets to model uncertainty in processing times and with the target of finding solutions that perform well with respect to both

Computaci�n Evolutiva para Resoluci�n de CSPs

Ibmrd, 2003

Benchmarks for Fuzzy Job Shop Problems

Information Sciences, 2016

The fuzzy job shop scheduling problem with makespan minimisation is a problem with a significant ... more The fuzzy job shop scheduling problem with makespan minimisation is a problem with a significant presence in the scientific literature. However, a common meaningful comparison base is missing for such problem. This work intends to fill the gap in this domain by reviewing existing benchmarks as well as proposing new benchmark problems. First, we shall survey the existing test beds for the fuzzy job shop, analysing whether they are sufficiently varied and, most importantly, whether there is room for improvement on these instances-an essential requirement if the instances are to be useful for the scientific community in order to compare and develop new solving strategies. In the light of this analysis, we shall propose a new family of more challenging benchmark problems and provide lower bounds for the expected makespan of each instance as well as reference makespan values obtained with a memetic algorithm from the literature. The resulting benchmark will be made available so as to facilitate experiment reproducibility and encourage research competition.

Heuristic Rules and Genetic Algorithms for Open Shop Scheduling Problem

Lecture Notes in Computer Science, 2004

Page 1. R. Conejo et al. (Eds.): CAEPIA-TTIA 2003, LNAI 3040, pp. 394403, 2004. © Springer-Verla... more

Genetic fuzzy schedules for charging electric vehicles

Computers & Industrial Engineering, 2018

This work tackles the problem of scheduling the charging of electric vehicles in a real-world cha... more This work tackles the problem of scheduling the charging of electric vehicles in a real-world charging station subject to a set of physical constraints, with the goal of minimising the total tardiness with respect to a desired departure date given for each vehicle. We model a variant of the problem that incorporates uncertainty in the charging times using fuzzy numbers. As solving method, we propose a genetic algorithm with tailor-made operators, in particular, a new chromosome evaluation method based on generating schedules from a priority vector. Finally, an experimental study avails the proposed genetic algorithm both in terms of algorithm convergence and quality of the obtained solutions.

Robust Multiobjective Optimisation for Fuzzy Job Shop Problems

Applied Soft Computing, 2016

In this paper we tackle a variant of the job shop scheduling problem with uncertain task duration... more In this paper we tackle a variant of the job shop scheduling problem with uncertain task durations modelled as fuzzy numbers. Our goal is to simultaneously minimise the schedule's fuzzy makespan and maximise its robustness. To this end, we consider two measures of solution robustness: a predictive one, prior to the schedule execution, and an empirical one, measured at execution. To optimise both the expected makespan and the predictive robustness of the fuzzy schedule we propose a multiobjective evolutionary algorithm combined with a novel dominance-based tabu search method. The resulting hybrid algorithm is then evaluated on existing benchmark instances, showing its good behaviour and the synergy between its components. The experimental results also serve to analyse the goodness of the predictive robustness measure, in terms of its correlation with simulations of the empirical measure.

A particle swarm solution based on lexicographical goal programming for a multiobjective fuzzy open shop problem

AI Communications

In the sequel, we consider a multiobjective open shop scheduling problem with uncertain durations... more In the sequel, we consider a multiobjective open shop scheduling problem with uncertain durations modelled as fuzzy numbers. Given crisp due dates, the objective is to minimise both the makespan and the maximum tardiness. We formulate the multiobjective problem as a fuzzy goal programming model based on lexicographical minimisation of expected values. The resulting problem is solved using a particle swarm optimization approach searching in the space of possibly active schedules. Experimental results are presented on several problem instances to evaluate the proposed method, illustrating its potential.

An advanced scatter search algorithm for solving job shops with sequence dependent and non-anticipatory setups

AI Communications

ABSTRACT

Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

Energies

Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem d... more Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.

Ordered structures for parallel rule-based computations : Section A: Computer system

International Journal of Computer Mathematics, 2001

In this paper we present an effective strategy to compute a partial order relation among the lite... more In this paper we present an effective strategy to compute a partial order relation among the literals of a query given by a conjuction of first order literals. This ordering expresses sufficient conditions in order for the subgoals of the query were independent each one to the others and hence they can be evaluated in parallel. To represent the partial

Efficient Producer/Consumer Parallelism in Logic Programming

Agp, 1996

A New Hybrid Genetic Algorithm for the Job Shop Scheduling Problem with Setup Times

Icaps, 2008

An Algorithm to Minimize Representations of Finite Order Relations

Ijcm, 1991

ABSTRACT

Computación Evolutiva para Resolución de CSPs

Inteligencia Artificial Revista Iberoamericana De Inteligencia Artificial, Nov 1, 2003

http:\\www.aic.uniovi.es Resumen Los problemas de Scheduling son un paradigma de la familia de pr... more http:\\www.aic.uniovi.es Resumen Los problemas de Scheduling son un paradigma de la familia de problemas CSP. En este artículo presentamos algunas técnicas de resolución mediante Algoritmos Genéticos. Consideramos en principio la aplicación de Algoritmos Genéticos convencionales, y luego vemos como la eficacia de éstos se puede mejorar notablemente con la utilización conjunta de otras técnicas también clásicas como son las reglas de prioridad, los heurísticos basados en la probabilidad y la búsqueda local. En particular mostramos mediante un estudio experimental como un esquema de búsqueda local mejora el rendimiento de un Algoritmo Genético convencional en la resolución del problema Job Shop Scheduling.

Ordered structures for parallel rule-based computations

International Journal of Computer Mathematics, May 23, 2012

In this paper we present an effective strategy to compute a partial order relation among the lite... more In this paper we present an effective strategy to compute a partial order relation among the literals of a query given by a conjuction of first order literals. This ordering expresses sufficient conditions in order for the subgoals of the query were independent each one to the others and hence they can be evaluated in parallel. To represent the partial

A New Local Search for the Job Shop Problem with Uncertain Durations

Icaps, 2008

In the sequel we consider the job shop scheduling problem with uncertain durations represented as... more In the sequel we consider the job shop scheduling problem with uncertain durations represented as triangular fuzzy numbers. We propose a new neighbourhood structure for local search, based on a new definition of critical path for fuzzy durations. A theoretical analysis of the proposed structure shows that it improves a previous one from the literature. It also shows that feasibility and connectivity hold, these being two highly desirable properties. Experimental results are reported which further illustrate the potential of the proposal.

A Parallel Programming Approach to Job Shop Scheduling Constrain Satisfaction Problems

Runtime bounds prediction for the Kemeny problem

Journal of Ambient Intelligence and Humanized Computing

The time required for solving the ranking aggregation problem using the Kemeny method increases f... more The time required for solving the ranking aggregation problem using the Kemeny method increases factorially with the number of alternatives to be ranked, which prevents its use when this number is large. Exact algorithms use domain information to discard rankings as possible solution, thus saving runtime. The amount of rankings that can be discarded varies for each profile and cannot be known beforehand. For profiles of rankings with large number of alternatives, the amount of rankings discarded highly affects the feasibility of the computation of Kemeny ranking. How to identify the profiles that are more time-consuming when finding the Kemeny ranking is not trivial. In this work we propose the use of machine learning models to predict how difficult is to obtain the Kemeny ranking in terms of runtime. The results obtained are promising, with values of the area under the curve metric over 80%. Furthermore, it is possible to extract from the proposed models the characteristics of the ...

Reducing the Computational Time for the Kemeny Method by Exploiting Condorcet Properties

Mathematics, 2021

Preference aggregation and in particular ranking aggregation are mainly studied by the field of s... more Preference aggregation and in particular ranking aggregation are mainly studied by the field of social choice theory but extensively applied in a variety of contexts. Among the most prominent methods for ranking aggregation, the Kemeny method has been proved to be the only one that satisfies some desirable properties such as neutrality, consistency and the Condorcet condition at the same time. Unfortunately, the problem of finding a Kemeny ranking is NP-hard, which prevents practitioners from using it in real-life problems. The state of the art of exact algorithms for the computation of the Kemeny ranking experienced a major boost last year with the presentation of an algorithm that provides searching time guarantee up to 13 alternatives. In this work, we propose an enhanced version of this algorithm based on pruning the search space when some Condorcet properties hold. This enhanced version greatly improves the performance in terms of runtime consumption.

The Borda Count as an Initial Threshold for Kemeny Ranking Aggregation

Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP), 2021

The need of establishing a consensus ranking from the preferences expressed by different voters a... more The need of establishing a consensus ranking from the preferences expressed by different voters arises in several contexts. The method proposed by Kemeny to this purpose is famously known due to its numerous fulfilled properties and intuitive interpretation, as it minimizes the number of pairwise comparisons in which the consensus ranking disagrees with the preferences given by the voters. Nevertheless, this method has a main drawback regarding its execution time, thus preventing its use in practice. There exist some other methods, such as the Borda Count, that can be computed in polynomial time, even though they do not fulfill as many intuitive properties as the Kemeny method. Here, we propose to use the Borda Count ranking as the initial solution of a Branchand-Bound algorithm for reducing the execution time of the Kemeny method. The presented experiments show that this approach leads to an improvement in execution time.

Multi-objective evolutionary algorithm for solving energy-aware fuzzy job shop problems

Soft Computing, 2020

A growing concern about the environmental impact of manufacturing processes and in particular, th... more A growing concern about the environmental impact of manufacturing processes and in particular, the associated energy consumption, has recently driven some researchers within the scheduling community to consider energy costs in addition to more traditional performance-related measures, such as satisfaction of due-date commitments. Recent research is also devoted to narrowing the gap between real-world applications and academic problems by handling uncertainty in some input data. In this paper we address the job shop scheduling problem, a well-known hard problem with many applications, using fuzzy sets to model uncertainty in processing times and with the target of finding solutions that perform well with respect to both

Computaci�n Evolutiva para Resoluci�n de CSPs

Ibmrd, 2003

Benchmarks for Fuzzy Job Shop Problems

Information Sciences, 2016

The fuzzy job shop scheduling problem with makespan minimisation is a problem with a significant ... more The fuzzy job shop scheduling problem with makespan minimisation is a problem with a significant presence in the scientific literature. However, a common meaningful comparison base is missing for such problem. This work intends to fill the gap in this domain by reviewing existing benchmarks as well as proposing new benchmark problems. First, we shall survey the existing test beds for the fuzzy job shop, analysing whether they are sufficiently varied and, most importantly, whether there is room for improvement on these instances-an essential requirement if the instances are to be useful for the scientific community in order to compare and develop new solving strategies. In the light of this analysis, we shall propose a new family of more challenging benchmark problems and provide lower bounds for the expected makespan of each instance as well as reference makespan values obtained with a memetic algorithm from the literature. The resulting benchmark will be made available so as to facilitate experiment reproducibility and encourage research competition.

Heuristic Rules and Genetic Algorithms for Open Shop Scheduling Problem

Lecture Notes in Computer Science, 2004

Page 1. R. Conejo et al. (Eds.): CAEPIA-TTIA 2003, LNAI 3040, pp. 394403, 2004. © Springer-Verla... more

Genetic fuzzy schedules for charging electric vehicles

Computers & Industrial Engineering, 2018

This work tackles the problem of scheduling the charging of electric vehicles in a real-world cha... more This work tackles the problem of scheduling the charging of electric vehicles in a real-world charging station subject to a set of physical constraints, with the goal of minimising the total tardiness with respect to a desired departure date given for each vehicle. We model a variant of the problem that incorporates uncertainty in the charging times using fuzzy numbers. As solving method, we propose a genetic algorithm with tailor-made operators, in particular, a new chromosome evaluation method based on generating schedules from a priority vector. Finally, an experimental study avails the proposed genetic algorithm both in terms of algorithm convergence and quality of the obtained solutions.

Robust Multiobjective Optimisation for Fuzzy Job Shop Problems

Applied Soft Computing, 2016

In this paper we tackle a variant of the job shop scheduling problem with uncertain task duration... more In this paper we tackle a variant of the job shop scheduling problem with uncertain task durations modelled as fuzzy numbers. Our goal is to simultaneously minimise the schedule's fuzzy makespan and maximise its robustness. To this end, we consider two measures of solution robustness: a predictive one, prior to the schedule execution, and an empirical one, measured at execution. To optimise both the expected makespan and the predictive robustness of the fuzzy schedule we propose a multiobjective evolutionary algorithm combined with a novel dominance-based tabu search method. The resulting hybrid algorithm is then evaluated on existing benchmark instances, showing its good behaviour and the synergy between its components. The experimental results also serve to analyse the goodness of the predictive robustness measure, in terms of its correlation with simulations of the empirical measure.

A particle swarm solution based on lexicographical goal programming for a multiobjective fuzzy open shop problem

AI Communications

In the sequel, we consider a multiobjective open shop scheduling problem with uncertain durations... more In the sequel, we consider a multiobjective open shop scheduling problem with uncertain durations modelled as fuzzy numbers. Given crisp due dates, the objective is to minimise both the makespan and the maximum tardiness. We formulate the multiobjective problem as a fuzzy goal programming model based on lexicographical minimisation of expected values. The resulting problem is solved using a particle swarm optimization approach searching in the space of possibly active schedules. Experimental results are presented on several problem instances to evaluate the proposed method, illustrating its potential.

An advanced scatter search algorithm for solving job shops with sequence dependent and non-anticipatory setups

AI Communications

ABSTRACT

Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

Energies

Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem d... more Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.

Ordered structures for parallel rule-based computations : Section A: Computer system

International Journal of Computer Mathematics, 2001

In this paper we present an effective strategy to compute a partial order relation among the lite... more In this paper we present an effective strategy to compute a partial order relation among the literals of a query given by a conjuction of first order literals. This ordering expresses sufficient conditions in order for the subgoals of the query were independent each one to the others and hence they can be evaluated in parallel. To represent the partial

Efficient Producer/Consumer Parallelism in Logic Programming

Agp, 1996

A New Hybrid Genetic Algorithm for the Job Shop Scheduling Problem with Setup Times

Icaps, 2008

An Algorithm to Minimize Representations of Finite Order Relations

Ijcm, 1991

ABSTRACT

Computación Evolutiva para Resolución de CSPs

Inteligencia Artificial Revista Iberoamericana De Inteligencia Artificial, Nov 1, 2003

http:\\www.aic.uniovi.es Resumen Los problemas de Scheduling son un paradigma de la familia de pr... more http:\\www.aic.uniovi.es Resumen Los problemas de Scheduling son un paradigma de la familia de problemas CSP. En este artículo presentamos algunas técnicas de resolución mediante Algoritmos Genéticos. Consideramos en principio la aplicación de Algoritmos Genéticos convencionales, y luego vemos como la eficacia de éstos se puede mejorar notablemente con la utilización conjunta de otras técnicas también clásicas como son las reglas de prioridad, los heurísticos basados en la probabilidad y la búsqueda local. En particular mostramos mediante un estudio experimental como un esquema de búsqueda local mejora el rendimiento de un Algoritmo Genético convencional en la resolución del problema Job Shop Scheduling.

Ordered structures for parallel rule-based computations

International Journal of Computer Mathematics, May 23, 2012

In this paper we present an effective strategy to compute a partial order relation among the lite... more In this paper we present an effective strategy to compute a partial order relation among the literals of a query given by a conjuction of first order literals. This ordering expresses sufficient conditions in order for the subgoals of the query were independent each one to the others and hence they can be evaluated in parallel. To represent the partial

A New Local Search for the Job Shop Problem with Uncertain Durations

Icaps, 2008

In the sequel we consider the job shop scheduling problem with uncertain durations represented as... more In the sequel we consider the job shop scheduling problem with uncertain durations represented as triangular fuzzy numbers. We propose a new neighbourhood structure for local search, based on a new definition of critical path for fuzzy durations. A theoretical analysis of the proposed structure shows that it improves a previous one from the literature. It also shows that feasibility and connectivity hold, these being two highly desirable properties. Experimental results are reported which further illustrate the potential of the proposal.

A Parallel Programming Approach to Job Shop Scheduling Constrain Satisfaction Problems