Articles de revista
http://hdl.handle.net/2117/3321
Mon, 31 Aug 2015 17:59:00 GMT2015-08-31T17:59:00ZWhen centers can fail: a close second opportunity
http://hdl.handle.net/2117/76239
When centers can fail: a close second opportunity
Albareda Sambola, Maria; Hinojosa, Yolanda; Marín, Alfredo; Puerto Albandoz, Justo
This paper presents the p-next center problem, which aims to locate p out of n centers so as to minimize the maximum cost of allocating customers to backup centers. In this problem it is assumed that centers can fail and customers only realize that their closest (reference) center has failed upon arrival. When this happens, they move to their backup center, i.e., to the center that is closest to the reference center. Hence, minimizing the maximum travel distance from a customer to its backup center can be seen as an alternative approach to handle humanitarian logistics, that hedges customers against severe scenario deteriorations when a center fails.
For this extension of the p-center problem we have developed several different integer programming formulations with their corresponding strengthenings based on valid inequalities and variable fixing. The suitability of these formulations for solving the p-next center problem using standard software is analyzed in a series of computational experiments. These experiments were carried out using instances taken from the previous discrete location literature.
Thu, 01 Oct 2015 00:00:00 GMThttp://hdl.handle.net/2117/762392015-10-01T00:00:00ZThe reliable p-median problem with at-facility service
http://hdl.handle.net/2117/28343
The reliable p-median problem with at-facility service
Albareda Sambola, Maria; Hinojosa, Yolanda; Puerto Albandoz, Justo
This paper deals with a discrete facility location model where service is provided at the facility sites. It is assumed that facilities can fail and customers do not have information on failures before reaching them. As a consequence, they may need to visit more than one facility, following an optimized search scheme, in order to get service. The goal of the problem is to locate p facilities in order to minimize the expected total travel cost. The paper presents two alternative mathematical programming formulations for this problem and proposes a matheuristic based on a network flow model to provide solutions to it. The computational burden of the presented formulations is tested and compared on a test-bed of instances.
Wed, 16 Sep 2015 00:00:00 GMThttp://hdl.handle.net/2117/283432015-09-16T00:00:00ZFix-and-relax approaches for controlled tabular adjustment
http://hdl.handle.net/2117/28326
Fix-and-relax approaches for controlled tabular adjustment
Baena, Daniel; Castro Pérez, Jordi; González Alastrué, José Antonio
Controlled tabular adjustment (CIA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Comput Oper Res 2011;38:1826-35 [23]). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances. (C) 2015 Elsevier Ltd. All rights reserved.
Mon, 01 Jun 2015 00:00:00 GMThttp://hdl.handle.net/2117/283262015-06-01T00:00:00ZMethodology for the economic optimisation of energy storage systems for frequency support in wind power plants
http://hdl.handle.net/2117/28095
Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants
Johnstone, Lewis; Díaz González, Francisco; Gomis Bellmunt, Oriol; Corchero García, Cristina; Cruz Zambrano, Miguel
This paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. The methodology was designed flexibly, so it can be applied to different energy markets and to include different ESS technologies. The methodology includes the formulation and solving of a Linear Programming (LP) problem.; The methodology was applied to the particular case of a 50 MW WPP, equipped with a Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the UK regular energy market and the UK frequency response market. Data for wind power generation and energy storage costs are estimated from literature.; Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3 MW and energy capacity of about 3 MW h would be enough to provide such service whilst maximising the incomes for the WPP operator considering the regular and frequency regulation UK markets. (C) 2014 Elsevier Ltd. All rights reserved.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2117/280952015-01-01T00:00:00ZA biased random-key genetic algorithm for the capacitated minimum spanning tree problem
http://hdl.handle.net/2117/27676
A biased random-key genetic algorithm for the capacitated minimum spanning tree problem
Ruiz Ruiz, Hector Efrain; Albareda Sambola, Maria; Fernández Aréizaga, Elena; Resende, Mauricio G. C.
This paper focuses on the capacitated minimum spanning tree(CMST)problem.Given a central
processor and a set of remote terminals with specified demands for traffic that must flow between the central processor and terminals,the goal is to design a minimum cost network to carry this demand.
Potential links exist between any pair of terminals and between the central processor and the terminals.
Each potential link can be included in the design at a given cost.The CMST problem is to design a
minimum-cost network connecting the terminals with the central processor so that the flow on any arc of the network is at most Q. A biased random-keygenetic algorithm(BRKGA)is a metaheuristic for combinatorial optimization which evolves a population of random vectors that encode solutions to the combinatorial optimization problem.This paper explores several solution encodings as well as different
strategies for some steps of the algorithm and finally proposes a BRKGA heuristic for the CMST problem.
Computational experiments are presented showing the effectivenes sof the approach:Seven newbest-
known solutions are presented for the set of benchmark instances used in the experiments.
Fri, 01 May 2015 00:00:00 GMThttp://hdl.handle.net/2117/276762015-05-01T00:00:00ZStochastic model for electrical loads in Mediterranean residential building: validation and applications
http://hdl.handle.net/2117/27403
Stochastic model for electrical loads in Mediterranean residential building: validation and applications
Ortiz, Joana Aina; Guarino, Francesco; Salom Tormo, Jaume; Corchero García, Cristina; Cellura, Maurizio
A major issue in modelling the electrical load of residential building is reproducing the variability between dwellings due to the stochastic use of different electrical equipment. In that sense and with the objective to reproduce this variability, a stochastic model to obtain load profiles of household electricity is developed. The model is based on a probabilistic approach and is developed using data from the Mediterranean region of Spain. A detailed validation of the model has been done, analysing and comparing the results with Spanish and European data. The results of the validation show that the model is able to reproduce the most important features of the residential electrical consumption, especially the particularities of the Mediterranean countries. The final part of the paper is focused on the potential applications of the models, and some examples are proposed. The model is useful to simulate a cluster of buildings or individual households. The model allows obtaining synthetic profiles representing the most important characteristics of the mean dwelling, by means of a stochastic approach. The inputs of the proposed model are adapted to energy labelling information of the electric devices. An example case is presented considering a dwelling with high performance equipment.
Thu, 01 May 2014 00:00:00 GMThttp://hdl.handle.net/2117/274032014-05-01T00:00:00ZRenewable energies in medium-term power planning
http://hdl.handle.net/2117/26280
Renewable energies in medium-term power planning
Marí Tomàs, Laura; Nabona Francisco, Narcís
The medium-term generation planning over a yearly horizon for generation portfolios including hydro generation and non-dispatchable renewables such as wind power and solar photovoltaic generation reveals how the penetration of these technologies reduces the share of other technologies and how it changes the profits and the profit spread in liberalized electricity markets. The matching of the load duration curves in different periods and the forced outages of generation units are here addressed through probabilistic methods and a heuristic is employed to guess which of the load-matching constraints may be active at the solution. There are well-established models for hydro generation in medium-term planning, but specific models are necessary to account for wind power and photovoltaic generation. A proposal for these is made in this work, which is suitable for use in the load duration curve matching through probabilistic methods. Moreover the stochasticity of the renewable sources requires the use of stochastic programming employing scenario trees, here developed using quasi-Monte Carlo techniques. Medium-term pumping schemes are also considered. Several realistic cases will be solved for two behavioral principles of a pure pool market: endogenous cartel and equilibrium.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2117/262802015-01-01T00:00:00ZComparative study of RPSALG algorithm for convex semi-infinite programming
http://hdl.handle.net/2117/24133
Comparative study of RPSALG algorithm for convex semi-infinite programming
Auslander, Alfred; Ferrer Biosca, Alberto; Goberna, Miguel Ángel; López Cerdá, Marco Antonio
The Remez penalty and smoothing algorithm (RPSALG) is a unified framework for penalty and smoothing methods for solving min-max convex semi-infinite programing problems, whose convergence was analyzed in a previous paper of three of the authors. In this paper we consider a partial implementation of RPSALG for solving ordinary convex semi-infinite programming problems. Each iteration of RPSALG involves two types of
auxiliary optimization problems: the Örst one consists of obtaining an approximate solution of some discretized convex problem, while the second one requires to solve a non-convex optimization problem involving the parametric constraints as objective function with the parameter as variable. In this paper we tackle the latter problem with a variant of the cutting angle method called ECAM, a global optimization procedure for solving Lipschitz programming problems. We implement di§erent variants of RPSALG which are compared with the unique publicly available SIP solver, NSIPS, on a battery of test problems.
Sat, 01 Mar 2014 00:00:00 GMThttp://hdl.handle.net/2117/241332014-03-01T00:00:00ZSolving DC programs using the cutting angle method
http://hdl.handle.net/2117/21984
Solving DC programs using the cutting angle method
Ferrer Biosca, Alberto; Bagirov, Adil; Beliakov, Gleb
In this paper, we propose a new algorithm for global minimization of functions represented as a difference of two convex functions. The proposed method is a derivative free method and it is designed by adapting the extended cutting angle method. We present preliminary results of numerical experiments using test problems with difference of convex objective functions and box-constraints. We also compare the proposed algorithm with a classical one that uses prismatical subdivisions.
Sat, 01 Feb 2014 00:00:00 GMThttp://hdl.handle.net/2117/219842014-02-01T00:00:00ZMedium-term load matching in power planning
http://hdl.handle.net/2117/20720
Medium-term load matching in power planning
Nabona Francisco, Narcís
The medium-term planning for a company participating in a pure pool market can be considered under different behavioral
principles: cartel, endogenous cartel with respect to hydro generation, and equilibrium. One of the important aspects of the model is the medium-term load matching, where load is represented by the load duration curves of each period into which the
medium-term horizon is subdivided.
The probabilistically exact Bloom and Gallant formulation of load matching could be employed, but its exponential number of
load-matching inequality constraints limits its use to small cases.
A heuristic has been proposed where only a small subset of the load-matching constraints, hopefully containing the active ones at the optimizer, is employed. This heuristic does not perform totally well with the more complex models, as those of endogenous cartel and equilibrium behavior, and a more comprehensive heuristic procedure is presented here. A well-known alternative method of medium-term load matching is the multi-block approximation to the load duration curve.
The three load-matching techniques mentioned above are here described and are compared, and computational results for realistic
systems are analyzed for the different behavioral models, showing the advantages of each procedure.
Thu, 18 Apr 2013 00:00:00 GMThttp://hdl.handle.net/2117/207202013-04-18T00:00:00Z