A characteristic of Data Envelopment Analysis (DEA) is to allow individual decision making units (DMUs) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, deters the comparison among DMUs on a common base. For dealing with this difficulty and assessing all the DMUs on the same scale, this paper proposes using a multiple objective linear programming (MOLP) approach based on scalarizing function for generating common set of weights under the DEA framework. This is an advantageous of the proposed approach against general approaches in the literature which are based on multiple objective nonlinear programming
Data envelopment analysis (DEA) is one of the most popular techniques for measuring relative efficie...
Conventional data envelopment analysis (DEA) stems from benefit/cost theory to evaluate the technica...
Provisions for controlling factor weights constitute a significant extension of the data envelopment...
A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DM...
A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DM...
Data envelopment analysis (DEA) is popularly used to evaluate relative efficiency among public or pr...
Data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homo...
The concept of efficiency as it applies to Decision Making Units (DMUs), solutions, alternatives pla...
Data envelopment analysis (DEA) is a common non-parametric frontier analysis method. The multiplier ...
Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the efficiency of Decision...
AbstractIt has been widely recognized that data envelopment analysis (DEA) lacks discrimination powe...
In order to rank all decision making units (DMUs) on the same basis, this paper proposes a multiobje...
summary:Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of...
The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Maki...
In aggregation of preferences system, each decision maker (DM) selects a subset of the alternative a...
Data envelopment analysis (DEA) is one of the most popular techniques for measuring relative efficie...
Conventional data envelopment analysis (DEA) stems from benefit/cost theory to evaluate the technica...
Provisions for controlling factor weights constitute a significant extension of the data envelopment...
A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DM...
A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DM...
Data envelopment analysis (DEA) is popularly used to evaluate relative efficiency among public or pr...
Data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homo...
The concept of efficiency as it applies to Decision Making Units (DMUs), solutions, alternatives pla...
Data envelopment analysis (DEA) is a common non-parametric frontier analysis method. The multiplier ...
Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the efficiency of Decision...
AbstractIt has been widely recognized that data envelopment analysis (DEA) lacks discrimination powe...
In order to rank all decision making units (DMUs) on the same basis, this paper proposes a multiobje...
summary:Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of...
The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Maki...
In aggregation of preferences system, each decision maker (DM) selects a subset of the alternative a...
Data envelopment analysis (DEA) is one of the most popular techniques for measuring relative efficie...
Conventional data envelopment analysis (DEA) stems from benefit/cost theory to evaluate the technica...
Provisions for controlling factor weights constitute a significant extension of the data envelopment...