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Title:
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CLOSETS TARGETS, BENCHMARKING AND DATA ENVELOPMENT ANALYSIS: A HEURISTIC ALGORITHM TO OBTAIN VALID SOLUTIONS FOR THE SHORTEST PROJECTION PROBLEM |
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Author(s):
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Clemente Benavente, Jose J. López-Espín, Juan Aparicio, Jesús T. Pastor, Domingo Giménez |
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ISBN:
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978-989-8533-25-8 |
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Editors:
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Hans Weghorn |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Data Envelopment Analysis, Heuristic Algorithms, Mathematical Programming, Efficiency Methodologies, Metaheuristic Techniques. |
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Type:
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Full Paper |
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First Page:
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69 |
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Last Page:
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76 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Data Envelopment Analysis (DEA) is a non-parametric technique to estimate the current level of efficiency of a set of entities. DEA provides information on how to remove inefficiency through the determination of benchmarking information. This paper is devoted to studying DEA models based on closest efficient targets, which are related to the shortest projection to the production frontier and allow inefficient firms to find the easiest way to improve their performance. Usually, these models have been solved by unsatisfactory methods since all of them are related, in some sense, to a combinatorial NP-hard problem. In this paper, the problem is approached by metaheuristic techniques. Due to the high number of restrictions of the problem, finding solutions to be used in the metaheuristic algorithm is difficult. Thus, this paper analyzes and compares some heuristic algorithms to obtain solutions for the problem. |
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