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Proceedings of the Third International Conference on Soft Computing for Problem Solving pp 785–792Cite as

Ant Colony Optimization Model for Discrete Tomography Problems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 258))

Abstract

Ant Colony Optimization (ACO) algorithms have been applied to get the solution of many hard discrete optimization problems. But ACO algorithms have not been applied to Discrete Tomography (DT) problems yet. In this paper, we propose a framework of ACO meta-heuristic for DT problems. Some variations in the framework have also been discussed.

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Authors and Affiliations

  1. Department of Mathematics, IIT Roorkee, Roorkee, India

    Divyesh Patel & Tanuja Srivastava

Authors
  1. Divyesh Patel
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  2. Tanuja Srivastava
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Corresponding author

Correspondence to Divyesh Patel .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  4. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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© 2014 Springer India

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Patel, D., Srivastava, T. (2014). Ant Colony Optimization Model for Discrete Tomography Problems. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_68

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  • DOI: https://doi.org/10.1007/978-81-322-1771-8_68

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1770-1

  • Online ISBN: 978-81-322-1771-8

  • eBook Packages: EngineeringEngineering (R0)

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