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Multi-objective Colliding Bodies Optimization

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Proceedings of Fifth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 436))

Abstract

Kaveh and Mahdavi proposed a new metaheuristic method in 2014 known as colliding bodies optimization (CBO). The algorithm is based on the principle of collision between bodies (each has a specific mass and velocity). The collision makes the bodies move toward the optimum position in the search space. This paper deals with the multi-objective formulation of CBO termed as MOCBO. Simulation studies on benchmark functions Schaffer N1, Schaffer N2, and Kursawe have demonstrated the superior performance of the MOCBO over multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance analysis are carried out for the proposed and benchmark algorithms in identical platforms using response matching between obtained and true Pareto front; the convergence matric, diversity matric, and computational efficiency achieved over fifty independent runs.

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Authors and Affiliations

  1. School of Basic Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, 751007, Orissa, India

    Arnapurna Panda &  Sabyasachi Pani

Authors
  1. Arnapurna Panda
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  2. Sabyasachi Pani
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Corresponding author

Correspondence to Arnapurna Panda .

Editor information

Editors and Affiliations

  1. Dept of Applied Sci & Eng, Indian Instit of Tech Roorkee, Roorkee, India

    Millie Pant

  2. Department of Mathematics, Indian Inst of Tech Roorkee, Roorkee, India

    Kusum Deep

  3. Chankyapuri, Rm 327, South Asian Univ, Akbar Bhawan, New Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics and Comp Sci, Liverpool Hope University, LIVERPOOL, United Kingdom

    Atulya Nagar

  5. Department of Mathematics, National Inst of Tech Silchar, Silchar, Assam, India

    Kedar Nath Das

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© 2016 Springer Science+Business Media Singapore

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Arnapurna Panda, Sabyasachi Pani (2016). Multi-objective Colliding Bodies Optimization. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_54

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  • DOI: https://doi.org/10.1007/978-981-10-0448-3_54

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0447-6

  • Online ISBN: 978-981-10-0448-3

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