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Linked Simulation Optimization Model for Evaluation of Optimal Bank Protection Measures

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Nature-Inspired Methods for Metaheuristics Optimization

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 16))

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Abstract

This work proposes a new methodology for determination of cost effective river training work using groynes. The proposed methodology links the two dimensional (2D) hydrodynamic model with genetic algorithm based optimization model. The hydrodynamic model uses Beam and Warming implicit finite difference scheme for solution of the governing equations of unsteady free surface flows in general coordinate system. The optimization model minimizes the total construction cost of the groyne system required for achieving desirable training of the river. Binary coded GA is used for solving the proposed optimization problem. The efficiency and field applicability of the developed model is evaluated using two different test problems. The first problem considers a hypothetical meandering channel and the second problem deals with a vulnerable reach of river Brahmaputra in India. The performance evaluation of the model shows potential of the developed model for field application.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Meghalaya, Shillong, Meghalaya, India

    Hriday Mani Kalita

  2. Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Rajib Kumar Bhattacharjya & Arup Kumar Sarma

Authors
  1. Hriday Mani Kalita
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  2. Rajib Kumar Bhattacharjya
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  3. Arup Kumar Sarma
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Editors and Affiliations

  1. Ecole Central de Nantes, Nantes cedex 3, France

    Fouad Bennis

  2. Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Rajib Kumar Bhattacharjya

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Kalita, H.M., Bhattacharjya, R.K., Sarma, A.K. (2020). Linked Simulation Optimization Model for Evaluation of Optimal Bank Protection Measures. In: Bennis, F., Bhattacharjya, R. (eds) Nature-Inspired Methods for Metaheuristics Optimization. Modeling and Optimization in Science and Technologies, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-030-26458-1_16

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  • DOI: https://doi.org/10.1007/978-3-030-26458-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26457-4

  • Online ISBN: 978-3-030-26458-1

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