Articles de revista
http://hdl.handle.net/2117/3321
20180421T09:59:51Z

Analysis of satellite constellations for the continuous coverage of ground regions
http://hdl.handle.net/2117/116370
Analysis of satellite constellations for the continuous coverage of ground regions
Dai, Guangming; Chen, Xiaoyu; Wang, Maocai; Fernández Aréizaga, Elena; Nguyen, Tuan Nam; Reinelt, Gerhard
This paper studies the problem of analyzing multisatellite constellations with respect to their coverage capacity of areas on Earth’s surface. The geometric configuration of constellation projection points on Earth’s surface is investigated. A geometric subdivision approach is described, and the coverage target area belonging to each satellite and its maximum circle radius are defined and calculated. Accordingly, the target area can be decomposed into subregions, and thus the multisatellite coverage problem is decomposed into a onesatellite coverage problem. An accurate and effective solution method is proposed that solves both continuous and discontinuous coverage problems for any type of ground area. In addition, a procedure for calculating satellite orbital parameters is also proposed. The performance of our approach is analyzed using the Globalstar system as an example, and it is shown that it compares favorably with the classical gridpoint technique and the longitude method.
20180417T08:33:26Z
Dai, Guangming
Chen, Xiaoyu
Wang, Maocai
Fernández Aréizaga, Elena
Nguyen, Tuan Nam
Reinelt, Gerhard
This paper studies the problem of analyzing multisatellite constellations with respect to their coverage capacity of areas on Earth’s surface. The geometric configuration of constellation projection points on Earth’s surface is investigated. A geometric subdivision approach is described, and the coverage target area belonging to each satellite and its maximum circle radius are defined and calculated. Accordingly, the target area can be decomposed into subregions, and thus the multisatellite coverage problem is decomposed into a onesatellite coverage problem. An accurate and effective solution method is proposed that solves both continuous and discontinuous coverage problems for any type of ground area. In addition, a procedure for calculating satellite orbital parameters is also proposed. The performance of our approach is analyzed using the Globalstar system as an example, and it is shown that it compares favorably with the classical gridpoint technique and the longitude method.

The shared customer collaboration vehicle routing problem
http://hdl.handle.net/2117/114847
The shared customer collaboration vehicle routing problem
Fernández Aréizaga, Elena; Roca Riu, Mireia; Speranza, M. Grazia
This paper introduces a new vehicle routing problem that arises in an urban area where several carriers operate and some of their customers have demand of service for more than one carrier. The problem, called Shared Customer Collaboration Vehicle Routing Problem, aims at reducing the overall operational cost in a collaboration framework among the carriers for the service of the shared customers. Alternative mathematical programming formulations are proposed for the problem that are solved with a branchandcut algorithm. Computational experiments on different sets of benchmark instances are run to assess the effectiveness of the formulations. Moreover, in order to estimate the savings coming from the collaboration, the optimal solutions are compared with the solutions obtained when carriers work independently from each other.
20180306T10:26:05Z
Fernández Aréizaga, Elena
Roca Riu, Mireia
Speranza, M. Grazia
This paper introduces a new vehicle routing problem that arises in an urban area where several carriers operate and some of their customers have demand of service for more than one carrier. The problem, called Shared Customer Collaboration Vehicle Routing Problem, aims at reducing the overall operational cost in a collaboration framework among the carriers for the service of the shared customers. Alternative mathematical programming formulations are proposed for the problem that are solved with a branchandcut algorithm. Computational experiments on different sets of benchmark instances are run to assess the effectiveness of the formulations. Moreover, in order to estimate the savings coming from the collaboration, the optimal solutions are compared with the solutions obtained when carriers work independently from each other.

The generalized arc routing problem
http://hdl.handle.net/2117/114843
The generalized arc routing problem
Araoz Durand, Julian Arturo; Fernández Aréizaga, Elena; Franquesa, Carles
This paper focuses on the generalized arc routing problem. This problem is stated on an undirected graph in which some clusters are defined as pairwisedisjoint connected subgraphs, and a route is sought that traverses at least one edge of each cluster. Broadly speaking, the generalized arc routing problem is the arc routing counterpart of the generalized traveling salesman problem, where the set of vertices of a given graph is partitioned into clusters and a route is sought that visits at least one vertex of each cluster. A mathematical programming formulation that exploits the structure of the problem and uses only binary variables is proposed. Facets and families of valid inequalities are presented for the polyhedron associated with the formulation and the corresponding separation problem studied. The numerical results of a series of computational experiments with an exact branch and cut algorithm are presented and analyzed.
The final publication is available at Springer via http://dx.doi.org/10.1007/s1175001704374
20180306T10:03:37Z
Araoz Durand, Julian Arturo
Fernández Aréizaga, Elena
Franquesa, Carles
This paper focuses on the generalized arc routing problem. This problem is stated on an undirected graph in which some clusters are defined as pairwisedisjoint connected subgraphs, and a route is sought that traverses at least one edge of each cluster. Broadly speaking, the generalized arc routing problem is the arc routing counterpart of the generalized traveling salesman problem, where the set of vertices of a given graph is partitioned into clusters and a route is sought that visits at least one vertex of each cluster. A mathematical programming formulation that exploits the structure of the problem and uses only binary variables is proposed. Facets and families of valid inequalities are presented for the polyhedron associated with the formulation and the corresponding separation problem studied. The numerical results of a series of computational experiments with an exact branch and cut algorithm are presented and analyzed.

A branchandprice algorithm for the Aperiodic MultiPeriod Service Scheduling Problem
http://hdl.handle.net/2117/114681
A branchandprice algorithm for the Aperiodic MultiPeriod Service Scheduling Problem
Fernández Aréizaga, Elena; Kalcsics, Jörg; Núñez del Toro, Alma Cristina
This paper considers the multiperiod service scheduling problem with an aperiodic service policy. In this problem, a set of customers who periodically require service over a finite time horizon is given. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers that can be served per period. With an aperiodic policy, customers may be served before the period were the service would be due. Two criteria are jointly considered in this problem: the total number of operators, and the total number of aheadoftime periods. The task is to determine the service periods for each customer in such a way that the service requests of the customers are fulfilled and both criteria are minimized. A new integer programming formulation is proposed, which outperforms an existing formulation. Since the computational effort required to obtain solutions considerably increases with the size of the instances, we also present a reformulation suitable for column generation, which is then integrated within a branchandprice algorithm. Computational experiments highlight the efficiency of this algorithm for the larger instances.
20180301T12:01:40Z
Fernández Aréizaga, Elena
Kalcsics, Jörg
Núñez del Toro, Alma Cristina
This paper considers the multiperiod service scheduling problem with an aperiodic service policy. In this problem, a set of customers who periodically require service over a finite time horizon is given. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers that can be served per period. With an aperiodic policy, customers may be served before the period were the service would be due. Two criteria are jointly considered in this problem: the total number of operators, and the total number of aheadoftime periods. The task is to determine the service periods for each customer in such a way that the service requests of the customers are fulfilled and both criteria are minimized. A new integer programming formulation is proposed, which outperforms an existing formulation. Since the computational effort required to obtain solutions considerably increases with the size of the instances, we also present a reformulation suitable for column generation, which is then integrated within a branchandprice algorithm. Computational experiments highlight the efficiency of this algorithm for the larger instances.

Multidepot rural postman problems
http://hdl.handle.net/2117/114231
Multidepot rural postman problems
Fernández Aréizaga, Elena; Rodríguez Pereira, Jessica
This paper studies multidepot rural postman problems on an undirected graph. These problems extend the wellknown undirected rural postman problem to the case where there are several depots instead of just one. Linear integer programming formulations that only use binary variables are proposed for the problem that minimizes the overall routing costs and for the model that minimizes the length of the longest route. An exact branchandcut algorithm is presented for each considered model, where violated constraints of both types are separated in polynomial time. Despite the difficulty of the problems, the numerical results from a series of computational experiments with various types of instances illustrate a quite good behavior of the algorithms. When the overall routing costs are minimized, over 43 % of the instances were optimally solved at the root node, and 95 % were solved at termination, most of them with a small additional computational effort. When the length of the longest route is minimized, over 25 % of the instances were optimally solved at the root node, and 99 % were solved at termination.
The final publication is available at Springer via http://dx.doi.org/10.1007/s117500160434z
20180219T10:55:51Z
Fernández Aréizaga, Elena
Rodríguez Pereira, Jessica
This paper studies multidepot rural postman problems on an undirected graph. These problems extend the wellknown undirected rural postman problem to the case where there are several depots instead of just one. Linear integer programming formulations that only use binary variables are proposed for the problem that minimizes the overall routing costs and for the model that minimizes the length of the longest route. An exact branchandcut algorithm is presented for each considered model, where violated constraints of both types are separated in polynomial time. Despite the difficulty of the problems, the numerical results from a series of computational experiments with various types of instances illustrate a quite good behavior of the algorithms. When the overall routing costs are minimized, over 43 % of the instances were optimally solved at the root node, and 95 % were solved at termination, most of them with a small additional computational effort. When the length of the longest route is minimized, over 25 % of the instances were optimally solved at the root node, and 99 % were solved at termination.

Minimum Spanning Trees with neighborhoods: mathematical programming formulations and solution methods
http://hdl.handle.net/2117/114229
Minimum Spanning Trees with neighborhoods: mathematical programming formulations and solution methods
Blanco, Víctor; Fernández Aréizaga, Elena; Puerto Albandoz, Justo
This paper studies Minimum Spanning Trees under incomplete information assuming that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a lqnorm. Two Mixed Integer Non Linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benderslike decomposition, which is embedded within an exact branchandcut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed.
20180219T08:48:19Z
Blanco, Víctor
Fernández Aréizaga, Elena
Puerto Albandoz, Justo
This paper studies Minimum Spanning Trees under incomplete information assuming that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a lqnorm. Two Mixed Integer Non Linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benderslike decomposition, which is embedded within an exact branchandcut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed.

Stochastic optimal generation bid to electricity markets with emissions risk constraints
http://hdl.handle.net/2117/114024
Stochastic optimal generation bid to electricity markets with emissions risk constraints
Heredia, F.Javier (Francisco Javier); Cifuentes Rubiano, Julián; Corchero García, Cristina
There are many factors that influence the dayahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossilfueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the mediumterm derivative commitments in the optimal generation bidding strategy for the dayahead electricity market. Two different technologies have been considered: the highemission technology of thermal coal units and the lowemission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the dayahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as ValueatRisk (VaR) and Conditional ValueatRisk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit's optimal generation bid to the wholesale electricity market such that it maximizes the longterm profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP's effects on the expected profits and the optimal generation bid.
© <year>. This manuscript version is made available under the CCBYNCND 4.0 license http://creativecommons.org/licenses/byncnd/4.0/
20180212T09:39:09Z
Heredia, F.Javier (Francisco Javier)
Cifuentes Rubiano, Julián
Corchero García, Cristina
There are many factors that influence the dayahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossilfueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the mediumterm derivative commitments in the optimal generation bidding strategy for the dayahead electricity market. Two different technologies have been considered: the highemission technology of thermal coal units and the lowemission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the dayahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as ValueatRisk (VaR) and Conditional ValueatRisk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit's optimal generation bid to the wholesale electricity market such that it maximizes the longterm profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP's effects on the expected profits and the optimal generation bid.

Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem
http://hdl.handle.net/2117/113316
Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem
Fernández Aréizaga, Elena; Pozo, Miguel Angel; Puerto Albandoz, Justo; Scozzari, Andre
Rework adversely impacts the performance of building projects. In this study, data were analyzed from 788 construction incidents in 40 Spanish building projects to determine the effects of project and managerial characteristics on rework costs. Finally, regression analysis was used to understand the relationships among contributing factors and to develop a model for rework prediction. Interestingly, the rework prediction model showed that only the original contract value (OCV) and the project location in relation to the company’s headquarters contributed to the regression model. Project type, type of organization, type of contract, and original contract duration (OCD), which represents the magnitude and complexity of a project, were represented by the OCV. This model for rework prediction based on original project conditions enables strategies to be put in place prior to the start of construction, to minimize uncertainties, to reduce impacts on project cost and schedule, and, thus, to improve productivity.
20180129T11:51:26Z
Fernández Aréizaga, Elena
Pozo, Miguel Angel
Puerto Albandoz, Justo
Scozzari, Andre
Rework adversely impacts the performance of building projects. In this study, data were analyzed from 788 construction incidents in 40 Spanish building projects to determine the effects of project and managerial characteristics on rework costs. Finally, regression analysis was used to understand the relationships among contributing factors and to develop a model for rework prediction. Interestingly, the rework prediction model showed that only the original contract value (OCV) and the project location in relation to the company’s headquarters contributed to the regression model. Project type, type of organization, type of contract, and original contract duration (OCD), which represents the magnitude and complexity of a project, were represented by the OCV. This model for rework prediction based on original project conditions enables strategies to be put in place prior to the start of construction, to minimize uncertainties, to reduce impacts on project cost and schedule, and, thus, to improve productivity.

The flexible periodic vehicle routing problem
http://hdl.handle.net/2117/113269
The flexible periodic vehicle routing problem
Archetti, C; Fernández Aréizaga, Elena; Huerta Muñoz, Diana Lucia
This paper introduces the Flexible Periodic Vehicle Routing Problem (FPVRP) where a carrier has to establish a distribution plan to serve his customers over a planning horizon. Each customer has a total demand that must be served within the horizon and a limit on the maximum quantity that can be delivered at each visit. A fleet of homogeneous capacitated vehicles is available to perform the services and the objective is to minimize the total routing cost. The FPVRP can be seen as a generalization of the Periodic Vehicle Routing Problem (PVRP) which instead has fixed service frequencies and schedules and where the quantity delivered at each visit is fixed. Moreover, the FPVRP shares some common characteristics with the Inventory Routing Problem (IRP) where inventory levels are considered at each time period and, typically, an inventory cost is involved in the objective function. We present a worstcase analysis which shows the advantages of the FPVRP with respect to both PVRP and IRP. Moreover, we propose a mathematical formulation for the problem, together with some valid inequalities. Computational results show that adding flexibility improves meaningfully the routing costs in comparison with both PVRP and IRP.
20180126T13:42:27Z
Archetti, C
Fernández Aréizaga, Elena
Huerta Muñoz, Diana Lucia
This paper introduces the Flexible Periodic Vehicle Routing Problem (FPVRP) where a carrier has to establish a distribution plan to serve his customers over a planning horizon. Each customer has a total demand that must be served within the horizon and a limit on the maximum quantity that can be delivered at each visit. A fleet of homogeneous capacitated vehicles is available to perform the services and the objective is to minimize the total routing cost. The FPVRP can be seen as a generalization of the Periodic Vehicle Routing Problem (PVRP) which instead has fixed service frequencies and schedules and where the quantity delivered at each visit is fixed. Moreover, the FPVRP shares some common characteristics with the Inventory Routing Problem (IRP) where inventory levels are considered at each time period and, typically, an inventory cost is involved in the objective function. We present a worstcase analysis which shows the advantages of the FPVRP with respect to both PVRP and IRP. Moreover, we propose a mathematical formulation for the problem, together with some valid inequalities. Computational results show that adding flexibility improves meaningfully the routing costs in comparison with both PVRP and IRP.

Heuristic solucions to the facility location problem with general Bernoulli demands
http://hdl.handle.net/2117/111476
Heuristic solucions to the facility location problem with general Bernoulli demands
Albareda Sambola, Maria; Fernández Aréizaga, Elena; Saldanha da Gama, Francisco
In this paper, a heuristic procedure is proposed for the facility location problem with general Bernoulli demands. This is a discrete facility location problem with stochastic demands that can be formulated as a twostage stochastic program with recourse. In particular, facility locations and customer assignments must be decided here and now, i.e., before knowing the customers who will actually require to be served. In a second stage, service decisions are made according to the actual requests. The heuristic proposed consists of a greedy randomized adaptive search procedure followed by a path relinking. The heterogeneous Bernoulli demands make prohibitive the computational effort for evaluating feasible solutions. Thus the expected cost of a feasible solution is simulated when necessary. The results of extensive computational tests performed for evaluating the quality of the heuristic are reported, showing that highquality feasible solutions can be obtained for the problem in fairly small computational times.
20171201T15:29:15Z
Albareda Sambola, Maria
Fernández Aréizaga, Elena
Saldanha da Gama, Francisco
In this paper, a heuristic procedure is proposed for the facility location problem with general Bernoulli demands. This is a discrete facility location problem with stochastic demands that can be formulated as a twostage stochastic program with recourse. In particular, facility locations and customer assignments must be decided here and now, i.e., before knowing the customers who will actually require to be served. In a second stage, service decisions are made according to the actual requests. The heuristic proposed consists of a greedy randomized adaptive search procedure followed by a path relinking. The heterogeneous Bernoulli demands make prohibitive the computational effort for evaluating feasible solutions. Thus the expected cost of a feasible solution is simulated when necessary. The results of extensive computational tests performed for evaluating the quality of the heuristic are reported, showing that highquality feasible solutions can be obtained for the problem in fairly small computational times.