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Genetic Algorithms, a Nature-Inspired Tool: Review of Applications in Supply Chain Management

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Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 335))

Abstract

The use of genetic algorithm for supply chain management with its ability to evolve solutions, handle uncertainty, and perform optimization remains to be a leading field of study. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, this paper presents a review of existing research activities inspired by the genetic algorithm application in supply chain management (SCM) aimed at presenting key research themes, trends, and directions of future research.

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  1. Indian Institute of Technology Roorkee, Roorkee, India

    Sunil Kumar Jauhar & Millie Pant

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  1. Sunil Kumar Jauhar
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Correspondence to Sunil Kumar Jauhar .

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  1. Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

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

    Kusum Deep

  3. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

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

    Jagdish Chand Bansal

  5. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

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Jauhar, S.K., Pant, M. (2015). Genetic Algorithms, a Nature-Inspired Tool: Review of Applications in Supply Chain Management. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2217-0_7

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