L'aprenentatge basat en problemes en models híbrids de docència-aprenentatge

La Facultat de Ciències de la Salut i de la Vida ha utilitzat des de 2004 la metodologia d'aprenentatge basat en problemes (en endavant ABP) com a mètode docent en els seus estudis de Biologia. En aquest període hem après algunes de les claus de l'aplicació del mètode en els nostres estudis. En primer lloc, cal disposar d'elements formatius que afavoreixin la formació dels tutors que participin en el projecte. Per assolir aquest objectiu hem dissenyat un portal on els nostres professors poden disposar de materials útils per a la seva activitat, així com de documents que permetin entendre millor el que suposa l'ABP. En segon lloc, el projecte tenia l'objectiu de dissenyar i avaluar activitats que permetessin integrar les pràctiques de laboratori en la lògica de la resolució de problemes pròpia de l'ABP. En aquest sentit vam dissenyar dues activitats en el tercer curs de la llicenciatura que anomenaren aprenentatge basat en el laboratori (ABL). Per aquest motiu es van dissenyar problemes que tinguessin una primera part de resolució a l'aula en grup de tutoria i una segona que obligués els estudiants a realitzar experiments de laboratori dirigits a entendre i resoldre les qüestions plantejades al grup de tutoria. L'ABL-1 fou un projecte de biologia cel·lular i destinat a aprofundir en els mecanismes implicats en els fenòmens de diferenciació dels miòcits. L'ABL-2 era un projecte conjunt dels professors de Fisiologia vegetal, Bioestadística i Microbiologia. En aquest cas es desitjava que els estudiants plantegessin la resolució a un problema que suposava la manipulació genètica de cèl·lules vegetals per fer possible que produïssin una substància específica, l'escopolamina. Finalment els estudiants havien d'escriure un article original com a projecte final de cada ABL. Els resultats dels dos anys d'experimentació han esta altament satisfactoris, d'acord amb les enquestes completades per alumnes i professors.

A simulation-based algorithm for solving the resource-assignment problem in satellite telecommunication networks

This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

Solving a concrete sleepers production scheduling by genetic algorithms

PRECON S.A is a manufacturing company dedicated to produce prefabricatedconcrete parts to several industries as rail transportation andagricultural industries.Recently, PRECON signed a contract with RENFE,the Spanish Nnational Rail Transportation Company to manufacturepre-stressed concrete sleepers for siding of the new railways of the highspeed train AVE. The scheduling problem associated with the manufacturingprocess of the sleepers is very complex since it involves severalconstraints and objectives. The constraints are related with productioncapacity, the quantity of available moulds, satisfying demand and otheroperational constraints. The two main objectives are related withmaximizing the usage of the manufacturing resources and minimizing themoulds movements. We developed a deterministic crowding genetic algorithmfor this multiobjective problem. The algorithm has proved to be a powerfuland flexible tool to solve the large-scale instance of this complex realscheduling problem.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Statistical modelling of CSP solving algorithms performance

The goal of this work is to try to create a statistical model, based only on easily computable parameters from the CSP problem to predict runtime behaviour of the solving algorithms, and let us choose the best algorithm to solve the problem. Although it seems that the obvious choice should be MAC, experimental results obtained so far show, that with big numbers of variables, other algorithms perfom much better, specially for hard problems in the transition phase.

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable

Metaheuristics for the bus-driver scheduling problem

We present new metaheuristics for solving real crew scheduling problemsin a public transportation bus company. Since the crews of thesecompanies are drivers, we will designate the problem by the bus-driverscheduling problem. Crew scheduling problems are well known and severalmathematical programming based techniques have been proposed to solvethem, in particular using the set-covering formulation. However, inpractice, there exists the need for improvement in terms of computationalefficiency and capacity of solving large-scale instances. Moreover, thereal bus-driver scheduling problems that we consider can present variantaspects of the set covering, as for example a different objectivefunction, implying that alternative solutions methods have to bedeveloped. We propose metaheuristics based on the following approaches:GRASP (greedy randomized adaptive search procedure), tabu search andgenetic algorithms. These metaheuristics also present some innovationfeatures based on and genetic algorithms. These metaheuristics alsopresent some innovation features based on the structure of the crewscheduling problem, that guide the search efficiently and able them tofind good solutions. Some of these new features can also be applied inthe development of heuristics to other combinatorial optimizationproblems. A summary of computational results with real-data problems ispresented.

Heuristic procedures for solving the General Assembly Line Balancing Problem with Setups (GALBPS)

The General Assembly Line Balancing Problem with Setups (GALBPS) was recently defined in the literature. It adds sequence-dependent setup time considerations to the classical Simple Assembly Line Balancing Problem (SALBP) as follows: whenever a task is assigned next to another at the same workstation, a setup time must be added to compute the global workstation time, thereby providing the task sequence inside each workstation. This paper proposes over 50 priority-rule-based heuristic procedures to solve GALBPS, many of which are an improvement upon heuristic procedures published to date.

Improving Information Problem Solving skills in Secondary Education through embedded instruction

This empirical study consists in an investigation of the effects, on the development of Information Problem Solving (IPS) skills, of a long-term embedded, structured and supported instruction in Secondary Education. Forty secondary students of 7th and 8th grades (13–15 years old) participated in the 2-year IPS instruction designed in this study. Twenty of them participated in the IPS instruction, and the remaining twenty were the control group. All the students were pre- and post-tested in their regular classrooms, and their IPS process and performance were logged by means of screen capture software, to warrant their ecological validity. The IPS constituent skills, the web search sub-skills and the answers given by each participant were analyzed. The main findings of our study suggested that experimental students showed a more expert pattern than the control students regarding the constituent skill ‘defining the problem’ and the following two web search sub-skills: ‘search terms’ typed in a search engine, and ‘selected results’ from a SERP. In addition, scores of task performance were statistically better in experimental students than in control group students. The paper contributes to the discussion of how well-designed and well-embedded scaffolds could be designed in instructional programs in order to guarantee the development and efficiency of the students’ IPS skills by using net information better and participating fully in the global knowledge society.

Polynomial-time complexity for instances of the endomorphism problem in free groups

We say the endomorphism problem is solvable for an element W in a free group F if it can be decided effectively whether, given U in F, there is an endomorphism Φ of F sending W to U. This work analyzes an approach due to C. Edmunds and improved by C. Sims. Here we prove that the approach provides an efficient algorithm for solving the endomorphism problem when W is a two- generator word. We show that when W is a two-generator word this algorithm solves the problem in time polynomial in the length of U. This result gives a polynomial-time algorithm for solving, in free groups, two-variable equations in which all the variables occur on one side of the equality and all the constants on the other side.

Metodologia a seguir per la reconstrucció d’imatges mèdiques i la seva transformació en geometries mallades per a l’ús computacional

Estudi elaborat a partir d’una estada a l'Imperial College of London, Gran Bretanya, entre setembre i desembre 2006. Disposar d'una geometria bona i ben definida és essencial per a poder resoldre eficientment molts dels models computacionals i poder obtenir uns resultats comparables a la realitat del problema. La reconstrucció d'imatges mèdiques permet transformar les imatges obtingudes amb tècniques de captació a geometries en formats de dades numèriques . En aquest text s'explica de forma qualitativa les diverses etapes que formen el procés de reconstrucció d'imatges mèdiques fins a finalment obtenir una malla triangular per a poder‐la processar en els algoritmes de càlcul. Aquest procés s'inicia a l'escàner MRI de The Royal Brompton Hospital de Londres del que s'obtenen imatges per a després poder‐les processar amb les eines CONGEN10 i SURFGEN per a un entorn MATLAB. Aquestes eines les han desenvolupat investigadors del Bioflow group del departament d'enginyeria aeronàutica del Imperial College of London i en l'ultim apartat del text es comenta un exemple d'una artèria que entra com a imatge mèdica i surt com a malla triangular processable amb qualsevol programari o algoritme que treballi amb malles.

On the complexity of the Whitehead minimization problem

The Whitehead minimization problem consists in finding a minimum size element in the automorphic orbit of a word, a cyclic word or a finitely generated subgroup in a finite rank free group. We give the first fully polynomial algorithm to solve this problem, that is, an algorithm that is polynomial both in the length of the input word and in the rank of the free group. Earlier algorithms had an exponential dependency in the rank of the free group. It follows that the primitivity problem – to decide whether a word is an element of some basis of the free group – and the free factor problem can also be solved in polynomial time.

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.