Evaluation of Heuristics Using Data Envelopment Analysis

Chung-Cheng Jason Lu and Yen-Chun Jim Wu ()
Additional contact information
Chung-Cheng Jason Lu: Department of Industrial Engineering and Management, National Taipei University of Technology, 1 Section 3, Chung Hsiao East Road, Taipei, Taiwan
Yen-Chun Jim Wu: Department of Management, National SunYat-Sen University, 10 Leinhai Rd., Kaohsiung, Taiwan

International Journal of Information Technology & Decision Making (IJITDM), 2014, vol. 13, issue 04, 795-810

Abstract: This paper focuses on identifying relatively efficient configurations of algorithmic operators among a set of configurations in the development of heuristics or meta-heuristics. Each configuration is considered as a decision-making unit with multiple inputs and outputs. Then, data envelopment analysis (DEA) is adopted to evaluate relative and cross-efficiencies of a set of algorithmic configurations. The proposed approach differs from existing methods based on statistical tests in that multiple inputs and outputs are simultaneously considered in an integrated framework for the evaluation of algorithmic efficiency. A case study is presented to demonstrate the application of DEA for determining the efficient configurations of genetic algorithm operators. The evaluation results of two DEA models are also compared. The DEA evaluation results are consistent with those obtained by a commonly used statistical method.

Keywords: Data envelopment analysis; heuristics; efficiency evaluation (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622014500606
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:13:y:2014:i:04:n:s0219622014500606

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622014500606

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().