http://hdl.handle.net/2117/3093 2013-05-18T06:34:27Z 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" 2013-04-22T10:09:40Z 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. 2013-02-22T10:25:06Z 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. 2012-11-15T11:15:38Z 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. 2012-08-28T10:04:07Z 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. 2012-07-18T10:22:39Z 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. 2012-06-27T12:59:15Z 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. 2012-02-22T10:21:30Z 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. 2011-11-02T11:16:03Z 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. 2011-10-18T12:05:59Z http://hdl.handle.net/2117/13398 Title: Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids Authors: Kolodziej, Joanna; Xhafa Xhafa, Fatos 2011-09-30T14:07:43Z http://hdl.handle.net/2117/13379 Title: Foundations of ANTCYCLE: self-synchronized duty-cycling in mobile sensor networks Authors: Hernández Pibernat, Hugo; Blum, Christian Abstract: Ants are generally believed to follow an intensive work routine. Numerous tales and fables refer to ants as conscientious workers. Nevertheless, biologists have discovered that ants also rest for extended periods of time. This does not only hold for individual ants. Interestingly, ant colonies exhibit synchronized activity phases that result from self-organization. In this work, self-synchronization in ant colonies is taken as the inspiring source for a new mechanism of self-synchronized duty-cycling in mobile sensor networks. Hereby, we assume that sensor nodes are equipped with energy harvesting capabilities such as, for example, solar cells. We show that the proposed self-synchronization mechanism can be made adaptive depending on variable energy resources. The main objective of this paper is to study and explore the swarm intelligence foundations of self-synchronized dutycycling. With this purpose in mind, physical constraints such as packet collisions and packet loss are generally not considered. 2011-09-28T12:36:48Z http://hdl.handle.net/2117/13343 Title: Unification and matching on compressed terms Authors: Gascón Caro, Adrià; Godoy Balil, Guillem; Schmidt-Schauß, Manfred Abstract: Term unification plays an important role in many areas of computer science, especially in those related to logic. The universal mechanism of grammar-based compression for terms, in particular the so-called singleton tree grammars (STGAs), have recently drawn considerable attention. Using STGs, terms of exponential size and height can be represented in linear space. Furthermore, the term representation by directed acyclic graphs (dags) can be efficiently simulated. The present article is the result of an investigation on term unification and matching when the terms given as input are represented using different compression mechanisms for terms such as dags and singleton tree grammars. We describe a polynomial time algorithm for context matching with dags, when the number of different context variables is fixed for the problem. For the same problem, NP-completeness is obtained when the terms are represented using the more general formalism of singleton tree grammars. For first-order unification and matching polynomial time algorithms are presented, each of them improving previous results for those problems. 2011-09-26T21:28:56Z http://hdl.handle.net/2117/13260 Title: Sensor field: a computational model Authors: Álvarez Faura, M. del Carme; Duch Brown, Amalia; Gabarró Vallès, Joaquim; Serna Iglesias, María José Abstract: We introduce a formal model of computation for networks of tiny artifacts, the static synchronous sensor field model (SSSF) which considers that the devices communicate through a fixed communication graph and interact with the environment through input/output data streams. We analyze the performance of SSSFs solving two sensing problems the Average Monitoring and the Alerting problems. For constant memory SSSFs we show that the set of recognized languages is contained in DSPACE(n + m) where n is the number of nodes of the communication graph and m its number of edges. Finally we explore the capabilities of SSSFs having sensing and additional non-sensing constant memory devices. 2011-09-20T09:51:32Z http://hdl.handle.net/2117/13125 Title: The Maximum degree of series-parallel graphs Authors: Drmota, Michael; Giménez Llach, Omer; Noy Serrano, Marcos Abstract: We prove that the maximum degree Δn of a random series-parallel graph with n vertices satisfies Δn/ log n → c in probability, and EΔn ∼ c log n for a computable constant c > 0. The same kind of result holds for 2-connected series-parallel graphs, for outerplanar graphs, and for 2-connected outerplanar graphs. 2011-08-26T08:11:08Z http://hdl.handle.net/2117/13091 Title: Hybrid metaheuristics in combinatorial optimization: A survey Authors: Blum, Christian; Puchinger, Jakob; Raidl, Günther; Roli, Andrea Abstract: Research in metaheuristics for combinatorial optimization problems has lately experienced a noteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problem-oriented. Nowadays the focus is on solving the problem at hand in the best way possible, rather than promoting a certain metaheuristic. This has led to an enormously fruitful cross-fertilization of different areas of optimization. This cross-fertilization is documented by a multitude of powerful hybrid algorithms that were obtained by combining components from several different optimization techniques. Hereby, hybridization is not restricted to the combination of different metaheuristics but includes, for example, the combination of exact algorithms and metaheuristics. In this work we provide a survey of some of the most important lines of hybridization. The literature review is accompanied by the presentation of illustrative examples. 2011-08-23T09:01:24Z