Performance evaluation through DEA benchmarking adjusted to goals (2019). Omega, 87, 150-157.

José L. Ruiz (Miguel Hernández University of Elche) and Inmaculada Sirvent(Miguel Hernández University of Elche).

Abstract. Data Envelopment Analysis (DEA) is extended to the evaluation of performance of organizations within the framework of the implementation of plans for improvements that set management goals. Managers usually set goals without having any evidence that they will be achievable at the moment of conduct- ing performance evaluation or, on the contrary, they may set little too unambitious goals. Using DEA for the benchmarking ensures an evaluation in terms of targets that both are attainable and represent best practices. In addition, the approach we propose adjusts the DEA benchmarking to the goals in order to consider the policy of improvements that was pursued with the setting of such goals. From the method- ological point of view, the models that minimize the distance to the DEA strong efficient frontier are extended to incorporate goal information. Specifically, the models developed seek DEA targets that are as close as possible to both actual performances and management goals. To illustrate, we examine an example that is concerned with the evaluation of performance of public Spanish universities.

Keywords. Performance evaluation; Benchmarking; Goals; DEA; Target setting

Seminar of Sebastián Lozano

10 October, 2019
12:30 pma1:30 pm

Speaker: Sebastián Lozano (University of Sevilla)

Title: “DEA analysis of network processes (Network DEA): Models and applications”

Date: Thursday, October 10, 12:30 a.m.

Localication: CIO Seminar Room (Torretamarit Building)

Abstract. Conventional data wrap analysis (DEA) considers the production process as a black box, that is, as a unique process that performs the transformation of inputs into outputs. There are, however, DEA approaches that open that box and distinguish within it different threads, each with its own inputs and outputs, and usually with intermediate product flows between the threads. A fundamental characteristic, then, of this type of Network DEA (NDEA) approaches is that each thread has its own technology. DEA models, both multiplier and envelope type, can be formulated for these types of situations. There are variants regarding the notation used as well as the treatment of intermediate products. There are radial approaches, directional distance function (DDF), Network SBM, etc. You can also consider shared inputs and undesirable outputs. With regard to applications, these are numerous and range from the transport sector to the banking sector, hotel sector, sports, etc.

Seminar of Antonino Laudani

26 September, 2019
11:00 ama12:00 pm

Speaker: Antonino Laudani (Università Degli Studi Roma Tre)

Title: “Mathematics vs Photovoltaic systems”

Date: Thursday, September 26, 11:00 a.m.

Localication: Classrooms 0.1 and 0.2 of the CIO (Torretamarit Building)

Abstract. All the field of engineering are fullfilled by mathematic approaches and this is particularly true for the fields of electrical and electronic engineering. On the other hand, it is also true that in the case of Photovoltaic systems (with this term I indicate all the Photovoltaic objects from the small devices to the large power plants), there are still a lot of things that mathematicians can do to improve the analysis, the modelling and the design of them. In this talk, I will discuss the contribution given by mathematic techniques (from Lambert function to Least Square Problem solution, etc) applied to photovoltaics and their open problems. Mathematicians together with electrical and electronic enginers and computer science scientists can provide a fundamental contribution in the research advance.

Seminar of Annick Laruelle

27 September, 2019
12:30 pma1:30 pm

Speaker: Annick Laruelle (Basque Country University)

Title: “Cost-Benefit analysis in participatory budgeting”

Date: Friday, September 27, 12:30 a.m.

Localication: CIO Seminar Room (Torretamarit Building)

Abstract. In participatory budgeting, citizens are invited to vote on different projects. Those with the most votes are chosen and implemented. The voting rules used in practice are usually based on single winner elections. A shortcoming of using these rules is that they do not take into account the costs of the projects, although those costs may differ substantially. The aim of this study is to provide an algorithm for a decision support system adapted to participatory budgeting processes. It relies on two main principles: First, a costly project should require more votes than a cheap project in order to be adopted¡ second, it is important to satisfy as many participants as possible. The method is applied to the 2018 participatory budgeting of the city of Portugalete (Spain).

Lipschitz Modulus of the Optimal Value in Linear Programming (2019). Journal of Optimization Theory and Applications, 182, 133-152.

María Jesús Gisbert (Miguel Hernández University of Elche), María Josefa Cánovas (Miguel Hernández University of Elche), Juan Parra (Miguel Hernández University of Elche) and Fco. Javier Toledo (Miguel Hernández University of Elche).

Abstract. The present paper is devoted to the computation of the Lipschitz modulus of the optimal value function restricted to its domain in linear programming under different types of perturbations. In the first stage, we study separately perturbations of the right-hand side of the constraints and perturbations of the coefficients of the objective function. Secondly, we deal with canonical perturbations, i.e., right-hand side perturbations together with linear perturbations of the objective. We advance that an exact formula for the Lipschitz modulus in the context of right-hand side perturbations is provided, and lower and upper estimates for the corresponding moduli are also established in the other two perturbation frameworks. In both cases, the corresponding upper estimates are shown to provide the exact moduli when the nominal (original) optimal set is bounded. A key strategy here consists in taking advantage of the background on calmness in linear programming and providing the aimed Lipschitz modulus through the computation of a uniform calmness constant.

Keywords. Lipschitz modulus; Optimal value; Linear programming; Variational analysis; Calmness