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Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks

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Abstract

This paper presents a two-membered evolution strategy based approach to address the total rotation minimization problem (TRMP) pertaining to directional sensor networks. TRMP is an \(\mathcal {N}\mathcal {P}\)-hard problem. Performance of the proposed approach is enhanced by employing a pre-processing step that utilizes a constructive heuristic and the concept of opposite solutions. We have compared our approach with the best approach available in the literature. The experimental results demonstrate our approach to be highly effective with substantial gain in terms of solution quality, in comparison to the best approach available in the literature. However, our approach requires more time in comparison to this approach.

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Acknowledgements

Authors are grateful to the four anonymous reviewers for their valuable comments and suggestions which helped in improving the quality of this manuscript. The first author acknowledges the financial support received from the Council of Scientific & Industrial Research, Government of India in the form of a Senior Research Fellowship.

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  1. School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500 046, India

    Gaurav Srivastava & Alok Singh

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  1. Gaurav Srivastava
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  2. Alok Singh
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Correspondence to Alok Singh.

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Srivastava, G., Singh, A. Boosting an evolution strategy with a preprocessing step: application to group scheduling problem in directional sensor networks. Appl Intell 48, 4760–4774 (2018). https://doi.org/10.1007/s10489-018-1252-9

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