Due to various seasonal and monthly changes in electricity consumption and difficulties in modeling it with the conventional methods, a novel algorithm is proposed in this paper. This study presents an approach that uses Artificial Neural Network (ANN), Principal Component Analysis (PCA), Data Envelopment Analysis (DEA) and ANOVA methods to estimate and predict electricity demand for seasonal a...

The variable returns to scale data envelopment analysis (DEA) model is developed with a maintained hypothesis of convexity in input-output space. This hypothesis is not consistent with standard microeconomic production theory that posits an S-shape for the production frontier, i.e. for production technologies that obey the Regular Ultra Passum Law. Consequently, measures of technical efficiency...

In the existing DEA models, we have a centralized decision maker (DM) who supervises all the operating units. In this paper, we solve a problem in which the centralized DM encounters limited or constant resources for total inputs or total outputs. We establish a DEA target model that solves and deals with such a situation. In our model, we consider the decrease of total input consumption and th...

0377-2217/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.ejor.2010.07.001 * Corresponding author at: Manchester Business Sc E-mail address: [email protected] (J.B. Yang The purpose of assessing past performances and setting future targets for an organisation such as a bank branch is to find where the branch stands in comparison to its peers within the bank branch network and how to ...

Clinicians and hospital administrators rely on information models for healthcare management and decision-making. However, healthcare surgical performance measurements include both qualitative and quantitative data, often with conflicting and interdependent variables. As a result many statistical modeling approaches can break down with healthcare data. Other more resilient algorithms, such as Da...

this paper gives a new application of dea to evaluate the scheduling solutions of parallel processing. it evaluates the scheduling solutions of parallel processing using the non-convex dea model, fdh model. by introducing each solution of parallel processing scheduling as a dmu with some relevant inputs and outputs this paper shows that how the most efficient schedule(s) can be identified.

As a non-parametric technique, Data Envelopment Analysis (DEA) evaluates the relative efficiency of peer decision making units (DMUs) that have multiple inputs and outputs. In many situations, DMUs have a two-stage structure, where * Corresponding author. E-mail address: [email protected] (A. Ashrafi) 1436 A. Ashrafi, A. B. Jaafar, L. S. Lee and M. R. Abu Bakar the first stage uses inputs to ...

This research evaluates the connection between corruption, economic development, and insecurity in several Colombian departments. This chapter explores the dynamics of these variables using two empirical techniques: the Data Envelopment Analysis (DEA) and the Dynamic Panel Data Model (DPDM). DEA is performed to evaluate social performance in terms of corruption, economic development, and insecu...

This paper uses a DEA model of multi-unit eciency measurement to investigate the gains from regional analysis of ecient economic development. The model is applied to the Chinese city economic development data used by Charnes, Cooper, and Li in a recent issue of this journal to demonstrate the usefulness of alternative DEA-based measures in economic development policy. Assuming that Chinese ci...

This research evaluates the connection between corruption, economic development, and insecurity in several Colombian departments. This chapter explores the dynamics of these variables using two empirical techniques: the Data Envelopment Analysis (DEA) and the Dynamic Panel Data Model (DPDM). DEA is performed to evaluate social performance in terms of corruption, economic development, and insecu...