DSpace Collection:
http://hdl.handle.net/2117/3093
Sun, 20 Apr 2014 14:09:21 GMT2014-04-20T14:09:21Zwebmaster.bupc@upc.eduUniversitat Politècnica de Catalunya. Servei de Biblioteques i DocumentaciónoNon-linear rewrite closure and weak normalization
http://hdl.handle.net/2117/20443
Title: Non-linear rewrite closure and weak normalization
Authors: Creus López, Carles; Godoy Balil, Guillem; Massanes Basi, Francesc d'Assis; Tiwari, Ashish Kumar
Abstract: A rewrite closure is an extension of a term rewrite system with new rules, usually deduced by transitivity. Rewrite closures have the nice property that all rewrite derivations can be transformed into derivations of a simple form. This property has been useful for proving decidability results in term rewriting. Unfortunately, when the term rewrite system is not linear, the construction of a rewrite closure is quite challenging. In this paper, we construct a rewrite closure for term rewrite systems that satisfy two properties: the right-hand side term in each rewrite rule contains no repeated variable (right-linear) and contains no variable occurring at depth greater than one (right-shallow). The left-hand side term is unrestricted, and in particular, it may be non-linear. As a consequence of the rewrite closure construction, we are able to prove decidability of the weak normalization problem for right-linear right-shallow term rewrite systems. Proving this result also requires tree automata theory. We use the fact that right-shallow right-linear term rewrite systems are regularity preserving. Moreover, their set of normal forms can be represented with a tree automaton with disequality constraints, and emptiness of this kind of automata, as well as its generalization to reduction automata, is decidable. A preliminary version of this work was presented at LICS 2009.Tue, 22 Oct 2013 12:42:27 GMThttp://hdl.handle.net/2117/204432013-10-22T12:42:27ZCreus López, Carles; Godoy Balil, Guillem; Massanes Basi, Francesc d'Assis; Tiwari, Ashish KumarnoRewrite closure
Term rewriting
Tree automata
Weak normalizationA rewrite closure is an extension of a term rewrite system with new rules, usually deduced by transitivity. Rewrite closures have the nice property that all rewrite derivations can be transformed into derivations of a simple form. This property has been useful for proving decidability results in term rewriting. Unfortunately, when the term rewrite system is not linear, the construction of a rewrite closure is quite challenging. In this paper, we construct a rewrite closure for term rewrite systems that satisfy two properties: the right-hand side term in each rewrite rule contains no repeated variable (right-linear) and contains no variable occurring at depth greater than one (right-shallow). The left-hand side term is unrestricted, and in particular, it may be non-linear. As a consequence of the rewrite closure construction, we are able to prove decidability of the weak normalization problem for right-linear right-shallow term rewrite systems. Proving this result also requires tree automata theory. We use the fact that right-shallow right-linear term rewrite systems are regularity preserving. Moreover, their set of normal forms can be represented with a tree automaton with disequality constraints, and emptiness of this kind of automata, as well as its generalization to reduction automata, is decidable. A preliminary version of this work was presented at LICS 2009.Architectural exploration of large-scale hierarchical chip multiprocessors
http://hdl.handle.net/2117/20442
Title: Architectural exploration of large-scale hierarchical chip multiprocessors
Authors: Nikitin, Nikita; San Pedro Martín, Javier de; Cortadella Fortuny, Jordi
Abstract: The continuous scaling of nanoelectronics is increasing the complexity of chip multiprocessors (CMPs) and exacerbating the memory wall problem. As CMPs become more complex, the memory subsystem is organized into more hierarchical structures to better exploit locality. To efficiently discover promising architectures within the rapidly growing search space, exhaustive exploration is replaced with tools that implement intelligent search strategies. Moreover, faster analytical models are preferred to costly simulations for estimating the performance and power of CMP architectures. The memory traffic generated by CMP cores has a cyclic dependency with the latency of the memory subsystem, which critically affects the overall system performance. Based on this observation, a novel scalable analytical method is proposed to estimate the performance of highly parallel CMPs (hundreds or thousands of cores) with hierarchical interconnect networks. The method can use customizable probabilistic models and solves the cyclic dependencies between traffic and latency by using a fixed-point strategy. By using the analytical model as a performance and power estimator, an efficient metaheuristic-based search is proposed for the exploration of large design spaces. The proposed techniques are shown to be very accurate and a promising strategy when compared to the results obtained by simulation.Tue, 22 Oct 2013 12:34:01 GMThttp://hdl.handle.net/2117/204422013-10-22T12:34:01ZNikitin, Nikita; San Pedro Martín, Javier de; Cortadella Fortuny, JordinoAnalytical modeling
chip multiprocessing
design space exploration
metaheuristics
numerical methodsThe continuous scaling of nanoelectronics is increasing the complexity of chip multiprocessors (CMPs) and exacerbating the memory wall problem. As CMPs become more complex, the memory subsystem is organized into more hierarchical structures to better exploit locality. To efficiently discover promising architectures within the rapidly growing search space, exhaustive exploration is replaced with tools that implement intelligent search strategies. Moreover, faster analytical models are preferred to costly simulations for estimating the performance and power of CMP architectures. The memory traffic generated by CMP cores has a cyclic dependency with the latency of the memory subsystem, which critically affects the overall system performance. Based on this observation, a novel scalable analytical method is proposed to estimate the performance of highly parallel CMPs (hundreds or thousands of cores) with hierarchical interconnect networks. The method can use customizable probabilistic models and solves the cyclic dependencies between traffic and latency by using a fixed-point strategy. By using the analytical model as a performance and power estimator, an efficient metaheuristic-based search is proposed for the exploration of large design spaces. The proposed techniques are shown to be very accurate and a promising strategy when compared to the results obtained by simulation.Decidable classes of tree automata mixing local and global constraints modulo flat theories
http://hdl.handle.net/2117/20262
Title: Decidable classes of tree automata mixing local and global constraints modulo flat theories
Authors: Barguño, Luis; Creus López, Carles; Godoy Balil, Guillem; Jacquemard, Florent; Vacher, Camile
Abstract: We define a class of ranked tree automata TABG generalizing both the tree automata with local tests between brothers of Bogaert and Tison (1992) and with global equality and disequality constraints (TAGED) of Filiot et al. (2007). TABG can test for
equality and disequality modulo a given flat equational theory between brother subterms
and between subterms whose positions are defined by the states reached during a computation.
In particular, TABG can check that all the subterms reaching a given state are distinct. This constraint is related to monadic key constraints for XML documents,
meaning that every two distinct positions of a given type have different values. We prove decidability of the emptiness problem for TABG. This solves, in particular, the open question of the decidability of emptiness for TAGED. We further extend our result by allowing global arithmetic constraints for counting the number of occurrences of some state or the number of different equivalence classes of subterms (modulo a given flat equational theory) reaching some state during a computation. We also adapt the
model to unranked ordered terms. As a consequence of our results for TABG, we prove
the decidability of a fragment of the monadic second order logic on trees extended with predicates for equality and disequality between subtrees, and cardinality.Wed, 02 Oct 2013 11:49:06 GMThttp://hdl.handle.net/2117/202622013-10-02T11:49:06ZBarguño, Luis; Creus López, Carles; Godoy Balil, Guillem; Jacquemard, Florent; Vacher, CamilenoAutomata theory, Computability and decidability, Equivalence classes, Forestry, XMLWe define a class of ranked tree automata TABG generalizing both the tree automata with local tests between brothers of Bogaert and Tison (1992) and with global equality and disequality constraints (TAGED) of Filiot et al. (2007). TABG can test for
equality and disequality modulo a given flat equational theory between brother subterms
and between subterms whose positions are defined by the states reached during a computation.
In particular, TABG can check that all the subterms reaching a given state are distinct. This constraint is related to monadic key constraints for XML documents,
meaning that every two distinct positions of a given type have different values. We prove decidability of the emptiness problem for TABG. This solves, in particular, the open question of the decidability of emptiness for TAGED. We further extend our result by allowing global arithmetic constraints for counting the number of occurrences of some state or the number of different equivalence classes of subterms (modulo a given flat equational theory) reaching some state during a computation. We also adapt the
model to unranked ordered terms. As a consequence of our results for TABG, we prove
the decidability of a fragment of the monadic second order logic on trees extended with predicates for equality and disequality between subtrees, and cardinality.Reference databases for taxonomic assignment in metagenomics
http://hdl.handle.net/2117/20108
Title: Reference databases for taxonomic assignment in metagenomics
Authors: Santamaria, Monica; Fosso, Bruno; Consiglio, Arianna; De Caro, Giorigio; Grillo, Giorgio; Licciulli, Flavio; Liuni, Sabino; Marzano, Marinella; Alonso-Alemany, Daniel; Valiente Feruglio, Gabriel Alejandro; Pesole, Graziano
Abstract: Metagenomics is providing an unprecedented access to the environmental microbial diversity. The amplicon-based metagenomics approach involves the PCR-targeted sequencing of a genetic locus fitting different features. Namely, it must be ubiquitous in the taxonomic range of interest, variable enough to discriminate between different species but flanked by highly conserved sequences, and of suitable size to be sequenced through next-generation platforms. The internal transcribed spacers 1 and 2 (ITS1 and ITS2) of the ribosomal DNA operon and one or more hyper-variable regions of 16S ribosomal RNA gene are typically used to identify fungal and bacterial species, respectively.
In this context, reliable reference databases and taxonomies are crucial to sssign amplicon sequence reads to the correct phylogenetic ranks. Several resources provide consistent phylogenetic classification of publicly available 16S ribosomal DNA sequences, whereas the state of ribosomal internal transcribed spacers reference databases is notably less advanced. In this review, we aim to give an overview of existing reference resources for both types of markers, highlighting strengths and possible shortcomings of their use for metagenomics purposes. Moreover, we
present a new database, ITSoneDB, of well annotated and phylogenetically classified ITS1 sequences to be used as a reference collection in metagenomic studies of environmental fungal communities. ITSoneDB is available for download and browsing at http://itsonedb.ba.itb.cnr.it/.Mon, 09 Sep 2013 11:44:31 GMThttp://hdl.handle.net/2117/201082013-09-09T11:44:31ZSantamaria, Monica; Fosso, Bruno; Consiglio, Arianna; De Caro, Giorigio; Grillo, Giorgio; Licciulli, Flavio; Liuni, Sabino; Marzano, Marinella; Alonso-Alemany, Daniel; Valiente Feruglio, Gabriel Alejandro; Pesole, GrazianonoMetagenomics, reference database, ITS, 16S rRNA, microbial communitiesMetagenomics is providing an unprecedented access to the environmental microbial diversity. The amplicon-based metagenomics approach involves the PCR-targeted sequencing of a genetic locus fitting different features. Namely, it must be ubiquitous in the taxonomic range of interest, variable enough to discriminate between different species but flanked by highly conserved sequences, and of suitable size to be sequenced through next-generation platforms. The internal transcribed spacers 1 and 2 (ITS1 and ITS2) of the ribosomal DNA operon and one or more hyper-variable regions of 16S ribosomal RNA gene are typically used to identify fungal and bacterial species, respectively.
In this context, reliable reference databases and taxonomies are crucial to sssign amplicon sequence reads to the correct phylogenetic ranks. Several resources provide consistent phylogenetic classification of publicly available 16S ribosomal DNA sequences, whereas the state of ribosomal internal transcribed spacers reference databases is notably less advanced. In this review, we aim to give an overview of existing reference resources for both types of markers, highlighting strengths and possible shortcomings of their use for metagenomics purposes. Moreover, we
present a new database, ITSoneDB, of well annotated and phylogenetically classified ITS1 sequences to be used as a reference collection in metagenomic studies of environmental fungal communities. ITSoneDB is available for download and browsing at http://itsonedb.ba.itb.cnr.it/.Evaluation of struggle strategy in genetic algorithms for ground stations scheduling problem
http://hdl.handle.net/2117/19681
Title: Evaluation of struggle strategy in genetic algorithms for ground stations scheduling problem
Authors: Xhafa Xhafa, Fatos; Herrero, Xavier; Barolli, Admir; Barolli, Leonard; Takizawa, Makoto
Abstract: Ground station scheduling problem arises in spacecraft operations and aims to allocate ground stations to spacecraft to make possible the communication between operations teams and spacecraft systems. The problem belongs to the family of satellite scheduling for the specific case of mapping communications to ground stations. The allocation of a ground station to a mission (e.g. telemetry, tracking information, etc.) has a high cost, and automation of the process provides many benefits not only in terms of management, but in economic terms as well. The problem is known for its high complexity as it is an over-constrained problem. In this paper, we present the resolution of the problem through Struggle Genetic Algorithms – a version of GAs that distinguishes for its efficiency in maintaining the diversity of the population during genetic evolution. We present some computational results obtained with Struggle GA using the STK simulation toolkit, which showed the efficiency of the method in solving the problem.Wed, 26 Jun 2013 15:48:39 GMThttp://hdl.handle.net/2117/196812013-06-26T15:48:39ZXhafa Xhafa, Fatos; Herrero, Xavier; Barolli, Admir; Barolli, Leonard; Takizawa, MakotonoGround station scheduling, Satellite scheduling, Struggle Genetic Algorithms, Constraint programming, SimulationGround station scheduling problem arises in spacecraft operations and aims to allocate ground stations to spacecraft to make possible the communication between operations teams and spacecraft systems. The problem belongs to the family of satellite scheduling for the specific case of mapping communications to ground stations. The allocation of a ground station to a mission (e.g. telemetry, tracking information, etc.) has a high cost, and automation of the process provides many benefits not only in terms of management, but in economic terms as well. The problem is known for its high complexity as it is an over-constrained problem. In this paper, we present the resolution of the problem through Struggle Genetic Algorithms – a version of GAs that distinguishes for its efficiency in maintaining the diversity of the population during genetic evolution. We present some computational results obtained with Struggle GA using the STK simulation toolkit, which showed the efficiency of the method in solving the problem.P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic
http://hdl.handle.net/2117/19618
Title: P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic
Authors: Spaho, Evjola; Barolli, Leonard; Xhafa Xhafa, Fatos; Biberaj, A.; Shurdi, O.
Abstract: P2P systems are very important for future distributed systems and applications. In such systems, the computational burden of the system can be distributed to peer nodes of the system. Therefore, in decentralized systems users become themselves actors by sharing, contributing and controlling the resources of the system. This characteristic makes P2P systems very interesting for the development of decentralized applications. Data replication techniques are commonplace in P2P systems. Data replication means storing copies of the same data at multiple peers thus improving availability and scalability. The trustworthiness of peers also is very important for safe communication in P2P system. The trustworthiness of a peer can be evaluated based on the reputation and actual behaviour of peers to provide services to other peers. In this paper, we propose two fuzzy-based systems for data replication and peer trustworthiness for JXTA-Overlay P2P platform. The simulation results have shown that in the first system, replication factor increases proportionally with increase of number of documents per peer, replication percentage and scale of replication per peer parameters and the second system can be used successfully to select the most reliable peer candidate to execute the tasks.Fri, 21 Jun 2013 16:08:34 GMThttp://hdl.handle.net/2117/196182013-06-21T16:08:34ZSpaho, Evjola; Barolli, Leonard; Xhafa Xhafa, Fatos; Biberaj, A.; Shurdi, O.noData replication, Fuzzy system, JXTA-Overlay, P2P, TrustworthinessP2P systems are very important for future distributed systems and applications. In such systems, the computational burden of the system can be distributed to peer nodes of the system. Therefore, in decentralized systems users become themselves actors by sharing, contributing and controlling the resources of the system. This characteristic makes P2P systems very interesting for the development of decentralized applications. Data replication techniques are commonplace in P2P systems. Data replication means storing copies of the same data at multiple peers thus improving availability and scalability. The trustworthiness of peers also is very important for safe communication in P2P system. The trustworthiness of a peer can be evaluated based on the reputation and actual behaviour of peers to provide services to other peers. In this paper, we propose two fuzzy-based systems for data replication and peer trustworthiness for JXTA-Overlay P2P platform. The simulation results have shown that in the first system, replication factor increases proportionally with increase of number of documents per peer, replication percentage and scale of replication per peer parameters and the second system can be used successfully to select the most reliable peer candidate to execute the tasks.Ant colony optimization theory : a survey
http://hdl.handle.net/2117/18911
Title: Ant colony optimization theory : a survey
Authors: Dorigo, Marco; Blum, Christian
Abstract: Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an effort to build a theory. Tackling questions such as "how and why the method works" is important, because finding an answer may help in improving its applicability. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle. With this article we provide a survey on theoretical results on ant colony optimization. First, we review some convergence results. Then we discuss relations between ant colony optimization algorithms and other approximate methods for optimization. Finally, we focus on some research efforts directed at gaining a deeper understanding of the behavior of ant colony optimization algorithms. Throughout the paper we identify some open questions with a certain interest of being solved in the near future.
Description: "Theoretical Computer Science Top Cited Article 2005-2010"Mon, 22 Apr 2013 10:09:40 GMThttp://hdl.handle.net/2117/189112013-04-22T10:09:40ZDorigo, Marco; Blum, ChristiannoAnt colony optimization, Metaheuristics, Combinatorial optimization, Convergence, Stochastic gradient descent, Model-based search, Approximate algorithmsResearch on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an effort to build a theory. Tackling questions such as "how and why the method works" is important, because finding an answer may help in improving its applicability. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle. With this article we provide a survey on theoretical results on ant colony optimization. First, we review some convergence results. Then we discuss relations between ant colony optimization algorithms and other approximate methods for optimization. Finally, we focus on some research efforts directed at gaining a deeper understanding of the behavior of ant colony optimization algorithms. Throughout the paper we identify some open questions with a certain interest of being solved in the near future.Computation of several power indices by generating functions
http://hdl.handle.net/2117/17925
Title: Computation of several power indices by generating functions
Authors: Alonso Meijide, José María; Freixas Bosch, Josep; Molinero Albareda, Xavier
Abstract: In this paper we propose methods to compute the Deegan-Packel, the Public
Good, and the Shift power indices by generating functions for the particular
case of weighted voting games. Furthermore, we define a new power index
which combines the ideas of the Shift and the Deegan-Packel power indices and
also propose a method to compute it with generating functions. We conclude
by some comments about the complexity to compute these power indices.Fri, 22 Feb 2013 10:25:06 GMThttp://hdl.handle.net/2117/179252013-02-22T10:25:06ZAlonso Meijide, José María; Freixas Bosch, Josep; Molinero Albareda, XaviernoIn this paper we propose methods to compute the Deegan-Packel, the Public
Good, and the Shift power indices by generating functions for the particular
case of weighted voting games. Furthermore, we define a new power index
which combines the ideas of the Shift and the Deegan-Packel power indices and
also propose a method to compute it with generating functions. We conclude
by some comments about the complexity to compute these power indices.Coaching on new technologies: programming workshop on Android applications for Google phones
http://hdl.handle.net/2117/16927
Title: Coaching on new technologies: programming workshop on Android applications for Google phones
Authors: Blesa Aguilera, Maria Josep; Duch Brown, Amalia; Gabarró Vallès, Joaquim; Hernández, Hugo; Serna Iglesias, María José
Abstract: In this work we describe our experience teaching an innovative Android programming workshop organized by the Universitat Politècnica de Catalunya (UPC) within the AndroidEDU Google EMEA Program. The growing interest in Android has allowed us to apply proactive learning techniques with very good results. As teachers, this was a challenging experience, that has forced us to rethink our role, to create educational material
accordant with the new communication media (forums, YouTube, etc.), and to supply the lack of expertise with an interesting collaboration between teachers and students. After three semesters teaching this workshop, we are convinced that this is an experience to share since the results have far exceeded our expectations.Thu, 15 Nov 2012 11:15:38 GMThttp://hdl.handle.net/2117/169272012-11-15T11:15:38ZBlesa Aguilera, Maria Josep; Duch Brown, Amalia; Gabarró Vallès, Joaquim; Hernández, Hugo; Serna Iglesias, María JosénoAndroidEDU Google EMEA ProgramIn this work we describe our experience teaching an innovative Android programming workshop organized by the Universitat Politècnica de Catalunya (UPC) within the AndroidEDU Google EMEA Program. The growing interest in Android has allowed us to apply proactive learning techniques with very good results. As teachers, this was a challenging experience, that has forced us to rethink our role, to create educational material
accordant with the new communication media (forums, YouTube, etc.), and to supply the lack of expertise with an interesting collaboration between teachers and students. After three semesters teaching this workshop, we are convinced that this is an experience to share since the results have far exceeded our expectations.Iterated greedy algorithms for the maximal covering location problem
http://hdl.handle.net/2117/16393
Title: Iterated greedy algorithms for the maximal covering location problem
Authors: Rodríguez, Francisco J.; Blum, Christian; Lozano, Manuel; García Martínez, Carlos
Abstract: 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
constructive procedure. Iterated greedy algorithms have been applied
successfully to solve a considerable number of problems. With the aim of
providing additional results and insights along this line of research, this
paper proposes two new iterated greedy algorithms that incorporate two
innovative components: a population of solutions optimised in parallel
by the iterated greedy algorithm, and an improvement procedure that
explores a large neighbourhood by means of an exact solver. The benefits
of the proposal in comparison to a recently proposed decomposition
heuristic and a standalone exact solver are experimentally shown.Tue, 28 Aug 2012 10:04:07 GMThttp://hdl.handle.net/2117/163932012-08-28T10:04:07ZRodríguez, Francisco J.; Blum, Christian; Lozano, Manuel; García Martínez, CarlosnoMaximal covering location problemThe 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
constructive procedure. Iterated greedy algorithms have been applied
successfully to solve a considerable number of problems. With the aim of
providing additional results and insights along this line of research, this
paper proposes two new iterated greedy algorithms that incorporate two
innovative components: a population of solutions optimised in parallel
by the iterated greedy algorithm, and an improvement procedure that
explores a large neighbourhood by means of an exact solver. The benefits
of the proposal in comparison to a recently proposed decomposition
heuristic and a standalone exact solver are experimentally shown.Taxonomic assignment in metagenomics with TANGO
http://hdl.handle.net/2117/16286
Title: Taxonomic assignment in metagenomics with TANGO
Authors: Alonso-Alemany, Daniel; Clemente, José C.; Jansson, Jesper; Valiente Feruglio, Gabriel Alejandro
Abstract: One of the main computational challenges facing metagenomic analysis is the taxonomic identification of short DNA fragments. The combination of sequence alignment methods with taxonomic assignment based on consensus can provide an accurate estimate of the microbial diversity in a sample. In this note, we show how recent improvements to these consensus methods, as implemented in the latest release of the TANGO tool, can provide an improved estimate of diversity in simulated datasets.Wed, 18 Jul 2012 10:22:39 GMThttp://hdl.handle.net/2117/162862012-07-18T10:22:39ZAlonso-Alemany, Daniel; Clemente, José C.; Jansson, Jesper; Valiente Feruglio, Gabriel AlejandronoOne of the main computational challenges facing metagenomic analysis is the taxonomic identification of short DNA fragments. The combination of sequence alignment methods with taxonomic assignment based on consensus can provide an accurate estimate of the microbial diversity in a sample. In this note, we show how recent improvements to these consensus methods, as implemented in the latest release of the TANGO tool, can provide an improved estimate of diversity in simulated datasets.Complete voting systems with two types of voters: weightedness and counting
http://hdl.handle.net/2117/16145
Title: Complete voting systems with two types of voters: weightedness and counting
Authors: Freixas Bosch, Josep; Molinero Albareda, Xavier; Roura Ferret, Salvador
Abstract: We investigate voting systems with two classes of voters, for which there is a hierarchy giving each member of the stronger class more influence or important than each member of the weaker class. We deduce for voting systems one important counting fact that allows determining how many of them are for a given number of voters. In fact, the number of these systems follows a Fibonacci sequence with a smooth polynomial variation on the number of voters. On the other hand, we classify by means of some parameters which of these systems are weighted. This result allows us to state an asymptotic conjecture which is opposed to what occurs for symmetric games.Wed, 27 Jun 2012 12:59:15 GMThttp://hdl.handle.net/2117/161452012-06-27T12:59:15ZFreixas Bosch, Josep; Molinero Albareda, Xavier; Roura Ferret, SalvadornoWe investigate voting systems with two classes of voters, for which there is a hierarchy giving each member of the stronger class more influence or important than each member of the weaker class. We deduce for voting systems one important counting fact that allows determining how many of them are for a given number of voters. In fact, the number of these systems follows a Fibonacci sequence with a smooth polynomial variation on the number of voters. On the other hand, we classify by means of some parameters which of these systems are weighted. This result allows us to state an asymptotic conjecture which is opposed to what occurs for symmetric games.Solving the two-dimensional bin packing problem with a probabilistic multi-start heuristic
http://hdl.handle.net/2117/15300
Title: Solving the two-dimensional bin packing problem with a probabilistic multi-start heuristic
Authors: Baumgartner, Lukas; Schmid, Verena; Blum, Christian
Abstract: The two-dimensional bin packing problem (2BP) consists in packing a set of rectangular items into rectangular, equally-sized bins. The problem is NP-hard and has a multitude of real world applications. We consider the case where the items are oriented and guillotine cutting is free. In this paper we first present a review of well-know heuristics for the 2BP and then propose a new ILP model for the problem. Moreover, we develop a multi-start algorithm based on a probabilistic version of the LGFi heuristic from the literature. Results are compared to other well-known heuristics, using data sets provided in the literature. The obtained experimental results show that the proposed algorithm returns excellent solutions. With an average percentage deviation of 1.8% from the best know lower bounds it outperformes the other algorithms by 1.1% − 5.7%. Also for 3 of the 500 instances we tested a new upper bound was found.Wed, 22 Feb 2012 10:21:30 GMThttp://hdl.handle.net/2117/153002012-02-22T10:21:30ZBaumgartner, Lukas; Schmid, Verena; Blum, ChristiannoThe two-dimensional bin packing problem (2BP) consists in packing a set of rectangular items into rectangular, equally-sized bins. The problem is NP-hard and has a multitude of real world applications. We consider the case where the items are oriented and guillotine cutting is free. In this paper we first present a review of well-know heuristics for the 2BP and then propose a new ILP model for the problem. Moreover, we develop a multi-start algorithm based on a probabilistic version of the LGFi heuristic from the literature. Results are compared to other well-known heuristics, using data sets provided in the literature. The obtained experimental results show that the proposed algorithm returns excellent solutions. With an average percentage deviation of 1.8% from the best know lower bounds it outperformes the other algorithms by 1.1% − 5.7%. Also for 3 of the 500 instances we tested a new upper bound was found.Large neighbourhood search algorithms for the founder sequence reconstruction problem
http://hdl.handle.net/2117/13711
Title: Large neighbourhood search algorithms for the founder sequence reconstruction problem
Authors: Roli, Andrea; Benedettini, Stefano; Stützle, Thomas; Blum, Christian
Abstract: The reconstruction of founder genetic sequences of a population is a relevant issue in evolutionary biology research. The problem consists in finding a biologically plausible set of genetic sequences (founders), which can be recombined to obtain the genetic sequences of the individuals of a given population. The reconstruction of these sequences can be modelled as a combinatorial optimisation problem in which one has to find a set of genetic sequences such that the individuals of the population under study can be obtained by recombining founder sequences minimising the number of recombinations. This problem is called the founder sequence reconstruction problem. Solving this problem can contribute to research in understanding the origins of specific genotypic traits. In this paper, we present large neighbourhood search algorithms to tackle this problem. The proposed algorithms combine a stochastic local search with a branch-and-bound algorithm devoted to neighbourhood exploration. The developed algorithms are thoroughly evaluated on three different benchmark sets and they establish the new state of the art for realistic problem instances.Wed, 02 Nov 2011 11:16:03 GMThttp://hdl.handle.net/2117/137112011-11-02T11:16:03ZRoli, Andrea; Benedettini, Stefano; Stützle, Thomas; Blum, ChristiannoThe reconstruction of founder genetic sequences of a population is a relevant issue in evolutionary biology research. The problem consists in finding a biologically plausible set of genetic sequences (founders), which can be recombined to obtain the genetic sequences of the individuals of a given population. The reconstruction of these sequences can be modelled as a combinatorial optimisation problem in which one has to find a set of genetic sequences such that the individuals of the population under study can be obtained by recombining founder sequences minimising the number of recombinations. This problem is called the founder sequence reconstruction problem. Solving this problem can contribute to research in understanding the origins of specific genotypic traits. In this paper, we present large neighbourhood search algorithms to tackle this problem. The proposed algorithms combine a stochastic local search with a branch-and-bound algorithm devoted to neighbourhood exploration. The developed algorithms are thoroughly evaluated on three different benchmark sets and they establish the new state of the art for realistic problem instances.Variable neighbourhood search for the variable sized bin packing problem
http://hdl.handle.net/2117/13560
Title: Variable neighbourhood search for the variable sized bin packing problem
Authors: Hemmelmayr, Vera C.; Schmid, Verena; Blum, Christian
Abstract: The variable sized bin packing problem is a generalisation of the one-dimensional bin packing problem. Given is a set of weighted items, which must be packed into a minimum-cost set of bins of variable sizes and costs. This problem has practical applications, for example, in packing, transportation planning, and cutting. In this work we propose a variable neighbourhood search metaheuristic for tackling the variable sized bin packing problem. The presented algorithm can be seen as a hybrid metaheuristic, because it makes use of lower bounding techniques and dynamic programming in various algorithmic components. An extensive experimentation on a diverse set of problem instances shows that the proposed algorithm is very competitive with current state-of-the-art approaches.Tue, 18 Oct 2011 12:05:59 GMThttp://hdl.handle.net/2117/135602011-10-18T12:05:59ZHemmelmayr, Vera C.; Schmid, Verena; Blum, ChristiannoThe variable sized bin packing problem is a generalisation of the one-dimensional bin packing problem. Given is a set of weighted items, which must be packed into a minimum-cost set of bins of variable sizes and costs. This problem has practical applications, for example, in packing, transportation planning, and cutting. In this work we propose a variable neighbourhood search metaheuristic for tackling the variable sized bin packing problem. The presented algorithm can be seen as a hybrid metaheuristic, because it makes use of lower bounding techniques and dynamic programming in various algorithmic components. An extensive experimentation on a diverse set of problem instances shows that the proposed algorithm is very competitive with current state-of-the-art approaches.