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Evaluation of Heuristics Using Data Envelopment Analysis

Author

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  • 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)

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.

Suggested Citation

  • Chung-Cheng Jason Lu & Yen-Chun Jim Wu, 2014. "Evaluation of Heuristics Using Data Envelopment Analysis," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 795-810.
    • Handle: RePEc:wsi:ijitdm:v:13:y:2014:i:04:n:s0219622014500606
    DOI: 10.1142/S0219622014500606
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    References listed on IDEAS

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    1. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, September.
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