An Iterated Three-Phase Search Approach for Solving the Cyclic Bandwidth Problem

The cyclic bandwidth problem (CBP) was initially introduced in the context of designing ring interconnection networks and has a number of other relevant applications, such as the design of computer networks and minimization of wire lengths in VLSI layout. However, the problem is computationally challenging since it belongs to the class of NP-hard problems. Existing studies on the CBP mainly focus on theoretical issues, and there are still very few practical methods devoted to this important problem. This paper fills the gap by introducing an iterated three-phase search approach for solving the CBP effectively. The proposed algorithm relies on three complementary search components to ensure a suitable balance of search intensification and diversification, guided by an enriched evaluation function. Computational assessments on a test-suite of 113 popular benchmark instances in the literature demonstrate the effectiveness of the proposed algorithm. In particular, it improves on 19 best-known computational results of the current best-performing algorithm for the problem and discovers 12 new record results (updated upper bounds). The key components of the proposed algorithm are investigated to shed light on their influences over the performance of the algorithm

Maximum Parsimony Phylogenetic Inference Using Simulated Annealing

International audienc

A Bottom-Up Implementation of Path-Relinking for Phylogenetic Reconstruction Applied to Maximum Parsimony

In this article we describe a bottom-up implementation of Path-Relinking for Phylogenetic Trees in the context of the resolution of the Maximum Parsimony problem with Fitch optimality criterion. This bottom-up implementation is compared to two versions of an existing top-down implementation. We show that our implementation is more efficient, more interesting to compare trees and to give an estimation of the distance between two trees in terms of the number of transformation

A Method for Systematic Adaptation and Synchronization of Healthcare Processes

International organizations, as the World Health Organization (WHO) and national governments are constantly defining (or modifying) new healthcare protocols and procedures. Those changes have a significant impact, on one side, on the organizational concerns of a great number of healthcare institutions and centers, and on the other side, on their health information systems that need to be adapted according to the new (or modified) procedures. Administrative workflows are commonly defined by a high level entity and they must then be applied on different institutions ruled by this high level entity. Those workflows must then be adapted to the particular circumstances of each institution, complying with the general regulations of the process established at the top level. This problem, called Hierarchical Adaptation Problem, also implies establishing the methods to evolve together the high level regulation. Such methods must maintain the consistency among the different levels by means of the propagation of the changes to all the different adaptations of the original workflow. To solve this problem, this work introduces the Hierarchical Adaptation Method. A method based on ontologies to define the rules that must be satisfied by a generic workflow to be considered adaptable to different application cases and the rules that must be satisfied by its adapted versions. Moreover, it provides the operations to facilitate both adaptation of administrative workflows and propagation of changes

An effective two-stage simulated annealing algorithm for the minimum linear arrangement problem

In this paper, an improved two-stage simulated annealing algorithm is presented for the minimum linear arrangement problem for graphs. This algorithm integrates several distinguished features including an efficient heuristic to generate good quality initial solutions, a highly discriminating evaluation function, a special neighborhood function and an effective cooling schedule. The algorithm is evaluated on a set of 30 well-known benchmark instances of the literature and compared with several state-of-the-art algorithms, showing improvements of 17 previous best results

An improved simulated annealing algorithm for bandwidth minimization

In this paper, a simulated annealing algorithm is presented for the bandwidth minimization problem for graphs. This algorithm is based on three distinguished features including an original internal representation of solutions, a highly discriminating evaluation function and an effective neighborhood. The algorithm is evaluated on a set of 113 well-known benchmark instances of the literature and compared with several state-of-the-art algorithms, showing improvements of some previous best results

Migration policies in dynamic island models

Dynamic island models are population-based algorithms for solving optimization problems, where the individuals of the population are distributed on islands. These subpopulations of individuals are processed by search algorithms on each island. In order to share information within this distributed search process, the individuals migrate from their initial island to another destination island at regular steps. In dynamic island models, the migration process evolves during the search according to the observed performance on the different islands. The purpose of this dynamic/adaptive management of the migrations is to send the individuals to the most promising islands, with regards to their current states. Therefore, our approach is related to the adaptive management of search operators in evolutionary algorithms. In this work, our main purpose is thus to precisely analyze dynamic migration policies. We propose a testing process that assigns gains to the algorithms applied on the islands in order to assess the adaptive ability of the migration policies, with regards to various scenarios. Instead of having one dynamic migration policy that is applied to the whole search process, as it has already been studied, we propose to associate a migration policy to each individual, which allows us to combine simultaneously different migration policies

Alternative evaluation functions for the cyclic bandwidth sum problem

One essential element for the successful application of metaheuristics is the evaluation function. It should be able to make fine distinctions among the potential solutions in order to avoid producing wide plateaus (valleys) in the fitness landscape, on which detecting a promising search direction could be hard for certain local search strategies. In the specific case of the cyclic bandwidth sum (CBS) problem, the heuristics reported have used directly the objective function of the optimization problem to assess the quality of potential solutions. Nevertheless, such a conventional function does not allow to efficiently establish preferences among distinct potential solutions. In order to cope with this important issue, three new more refined evaluation functions for the CBS problem are introduced in this paper. An in-depth comparative analysis considering the conventional and the three proposed evaluation functions is carried out and presented. It includes an assessment of their: (a) discrimination potential, (b) consistency with regard to the primary objective of the CBS problem, and (c) practical usefulness within two different algorithms, best improvement local search and iterated local search. A validation of the experimental results by means of a meticulous statistical significance analysis revealed that proposing more informative evaluation schemes for the CBS problem could be a useful means of improving the performance of metaheuristics. Indeed, our iterated local search implementation, using an alternative evaluation function, surpassed the best solutions yielded by the state-of-the-art algorithms and allow us to attain new better upper bounds for 14 out of 20 well-known benchmark instances

Situación de la tuberculosis en España, 2011. Red Nacional de Vigilancia Epidemiológica

En este boletín se presenta la situación de la tuberculosis en España con los datos procedentes de la Red Nacional de Vigilancia Epidemiológica (RENAVE) en 2011, así como los datos actualizados de los resultados de tratamiento correspondientes a los casos declarados en 2010. La tasa de incidencia de tuberculosis en 2011 fue de 14,63 casos por 100.000 habitantes, un 6,8% inferior a la del año 2010

Tabu search for the cyclic bandwidth problem

The Cyclic Bandwidth (CB) problem for graphs consists in labeling the vertices of a guest graph G by distinct vertices of a host cycle Cn (both of order n) in such a way that the maximum distance in the cycle between adjacent vertices in G is minimized. To the best of our knowledge, this is the first research work investigating the use of metaheuristic algorithms for solving this challenging combinatorial optimization problem in the case of general graphs. In this paper a new carefully devised Tabu Search   algorithm, called TScb, for finding near-optimal solutions for the CB problem is proposed. Different possibilities for its key components and input parameter values were carefully analyzed and tuned, in order to find the combination of them offering the best quality solutions to the problem at a reasonable computational effort. Extensive experimentation was carried out, using 113 standard benchmark instances, for assessing its performance with respect to a Simulated Annealing (SAcb) implementation. The experimental results show that there exists a statistically significant performance amelioration achieved by TScb with respect toSAcb in 90 out of 113 graphs (79.646%). It was also found that our TScb algorithm attains 56 optimal solutions and establishes new better upper bounds for the other 57 instances. Furthermore, these competitive results were obtained expending reasonable computational times