Scenario Cluster Lagrangian Decomposition in two stage stochastic mixed 0-1 optimization

In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.

On parallel computing for stochastic optimization models and algorithms

167 p.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

Computing abuse related damages in the case of new entry: An illustration for the Directory Enquiry Services market

A number of European countries, among which the UK and Spain, have opened up their Directory Enquiry Services (DQs, or 118AB) market to competition. We analyse the Spanish case, where both local and foreign firms challenged the incumbent as of April 2003. We argue that the incumbent had the ability to abuse its dominant position, and that it was a perfectly rational strategy. In short,the incumbent raised its rivals' costs directly by providing an inferior quality version of the (essential) input, namely the incumbent's subscribers' database. We illustrate how it is possible to quantify the effect of abuse in situation were the entrant has no previous history in the market. To do this, we use the UK experience to construct the relevant counterfactual, that is the "but for abuse" scenario. After controlling for relative prices and advertising intensity, we find that one of the foreign entrants achieved a Spanish market share of only half of what it would have been in the absence of abuse.

Generating cluster submodels from a multistage stochastic mixed integer optimization model using break stage

We present a scheme to generate clusters submodels with stage ordering from a (symmetric or a nonsymmetric one) multistage stochastic mixed integer optimization model using break stage. We consider a stochastic model in compact representation and MPS format with a known scenario tree. The cluster submodels are built by storing first the 0-1 the variables, stage by stage, and then the continuous ones, also stage by stage. A C++ experimental code has been implemented for reordering the stochastic model as well as the cluster decomposition after the relaxation of the non-anticipativiy constraints until the so-called breakstage. The computational experience shows better performance of the stage ordering in terms of elapsed time in a randomly generated testbed of multistage stochastic mixed integer problems.

Cluster analisiaren aplikazio bat ekonomian Donostiako auzoen ikerketa

Lan honekin Donostiako bizitza kalitatea ikertu nahi dute, hau da etxebizitzetako bizilagunen eta etxebizitzen egitura eta erabileraren arteko erlazio posiblea. Biztanle mota, etxebizitza mota eta Donostiako eremu homogeneoen arteko lotura bilatzen saiatuko dira, Aldagai Anitzeko Analisia, batez ere Osagai Nagusizko Analisia, erabiliz aldagai kopurua murrizteko eta faktore edo osagai gutxitan aldagaien informazio gehiena jasotzeko. Jarraian, Cluster aplikatuko dute auzo homogeneoen taldeak osatzeko.

Estrategias de Marketing para la gestión público-privada del comercio de Guipúzcoa. Un modelo basado en el análisis cluster.

Este artículo trata sobre el desarrollo de áreas comerciales en los alrededores de las ciudades y de cómo el centro urbano ha ido perdiendo atractivo comercial. Esta situación, común en la mayor parte de los países de nuestro entorno, plantea importantes problemas para el comercio tradicional de centro ciudad, que ve como gran parte de sus clientes optan por la oferta de la periferia, con la siguiente fuga de ingresos.

Towards a standard methodology to evaluate internal cluster validity indices

The evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.

Orígenes, elementos determinantes y resultados de un exitoso proceso de colaboración entre competidores y otros agentes: el cluster de la Alta Cocina Vasca

[ES] El País Vasco es internacionalmente reconocido por su gastronomía y sus grandes cocineros; de hecho, es el territorio del mundo con más estrellas Michelin por kilómetro cuadrado. Esta notoriedad e imagen repercuten muy positivamente en todo el sector gastronómico y en la imagen y proyección turística del País Vasco y se ha logrado gracias a la labor sostenida de un grupo inicial de cocineros, a los que siguieron otros, que realizan importantes esfuerzos de colaboración, sin dejar de competir entre ellos (tratándose de un claro ejemplo de coopetition). El análisis de la relación entre estos grandes cocineros vascos y su entorno, permite identificar un cluster que actualmente se encuentra en fase de madurez con un futuro esperanzador y que ha arrojado importantes beneficios al sector, a cada uno de sus integrantes y a la región en su conjunto muy especialmente en términos de innovación, notoriedad y reputación. Para la realización de este trabajo se ha utilizado, además de la revisión bibliográfica y documental pertinente, una metodología cualitativa, consistente en la realización de entrevistas en profundidad a los siete cocineros fundadores y patronos del Basque Culinary Center (primera Facultad Universitaria de Estudios Gastronómicos de Europa, dependiente de la Universidad de Mondragón). El trabajo es uno de los frutos extraídos de un contrato de colaboración entre el Instituto de Economía Aplicada a la empresa de la UPV/EHU e Innobasque (Agencia Vasca para la Innovación), en el que esta última fijó tanto los objetivos de la investigación como la metodología a utilizar.

Radio-aware service-level scheduling to minimize downlink traffic delay through Mobile Edge Computing

One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either speci c to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.

Design and implementation of a cloud computing adoption decision tool: Generating a cloud road

Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on "on-demand payment" for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: To ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible. Copyright: © 2015 Bildosola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Contributions to High-Throughput Computing Based on the Peer-to-Peer Paradigm

XII, 116 p.