A Heuristic Method on Extended Two-Stage Network Structures
Authors
Abstract:
Data Envelopment Analysis (DEA) as a non–parametric method is used to measure relative performance of organizational units. The aim of this paper is to develop a new model to evaluate the efficiency of a general two-stage network structures proposed by Li et al. (2012) for measuring the performance of Decision Making Units (DMUs). In addition, this paper expands the work of Li et al. (2012) and improves the heuristic search procedure to estimate the optimal solutions of non-linear centralized models. In order to evaluate the proposed model of this study, it has been applied to a case of regional Research and Development (R&D) system related to 30 provincial level regions in China. The experimental results compared with method developed by Li et al. (2012) show that the proposed method is efficient and has much lower computational complexity.
similar resources
Efficiency Measurement in Two-Stage Network Structures Considering Undesirable Outputs
Since data envelopment analysis (DEA) introduced in 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems. Recently DEA has been extended to examine the efficiency of decision making units (DMUs) with two-stage network structures or processes, where the outputs from the first stage are intermediate measures that make up the inputs of t...
full textairline hub-median network design by an extended two-stage stochastic programming method: a case study
the hub location decision is a long term investment and any changes in it take considerable time and money. in real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. the ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. in the two-stage stochastic programm...
full textA TWO-STAGE METHOD FOR DAMAGE DETECTION OF LARGE-SCALE STRUCTURES
A novel two-stage algorithm for detection of damages in large-scale structures under static loads is presented. The technique utilizes the vector of response change (VRC) and sensitivities of responses with respect to the elemental damage parameters (RSEs). It is shown that VRC approximately lies in the subspace spanned by RSEs corresponding to the damaged elements. The property is leveraged in...
full textefficiency measurement in two-stage network structures considering undesirable outputs
since data envelopment analysis (dea) introduced in 1970s, it has been widely applied to measure the efficiency of a wide variety of production and operation systems. recently dea has been extended to examine the efficiency of decision making units (dmus) with two-stage network structures or processes, where the outputs from the first stage are intermediate measures that make up the inputs of t...
full textA TWO-STAGE DAMAGE DETECTION METHOD FOR LARGE-SCALE STRUCTURES BY KINETIC AND MODAL STRAIN ENERGIES USING HEURISTIC PARTICLE SWARM OPTIMIZATION
In this study, an approach for damage detection of large-scale structures is developed by employing kinetic and modal strain energies and also Heuristic Particle Swarm Optimization (HPSO) algorithm. Kinetic strain energy is employed to determine the location of structural damages. After determining the suspected damage locations, the severity of damages is obtained based on variations of modal ...
full textTwo-stage network DEA-R based on value efficiency
It is essential for most organizations and financial institutes to be able to evaluate their decision-making units (DMUs), when there is only a ratio of inputs to outputs (or vice versa) available. In this paper, we will propose our two-stage DEA-R models, which are a combination of data envelopment analysis and ratio data, based on value efficiency. Integrating value efficiency into data envel...
full textMy Resources
Journal title
volume 3 issue 11
pages 91- 98
publication date 2017-10-23
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023