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An Artificial Physics Optimization Algorithm for Multi-Objective Problems Based on Virtual Force Sorting Proceedings

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6466))

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Abstract

In order to maintain the diversity of non-dominated solutions in multi-objective optimization algorithms efficiently the authors have proposed a multi-objective artificial physics optimization algorithm based on virtual force sorting (VFMOAPO). Adopting quick-sort idea, the individuals in non-dominated solutions set were sorted by the total virtual force exerting on the other individuals. So the non-dominated solution set was pruned and the individual with the maximal sum of virtual force exerting on the other individuals was selected as the global best solution. Some benchmark functions were tested for comparing the performance of VFMOAPO with MOPSO, NSGA and SPEA. The simulation results show the algorithm is feasible and competitive.

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References

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Author information

Authors and Affiliations

  1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China

    Yan Wang

  2. Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, China

    Yan Wang, Jian-chao Zeng & Ying Tan

Authors
  1. Yan Wang
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  2. Jian-chao Zeng
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  3. Ying Tan
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, India

    Bijaya Ketan Panigrahi

  2. Department of Electronics and Communication Engineering, Jadavpur University, 700032, Kolkata, West Bengal, India

    Swagatam Das

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  4. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

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© 2010 Springer-Verlag Berlin Heidelberg

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Wang, Y., Zeng, Jc., Tan, Y. (2010). An Artificial Physics Optimization Algorithm for Multi-Objective Problems Based on Virtual Force Sorting Proceedings. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_72

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  • DOI: https://doi.org/10.1007/978-3-642-17563-3_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17562-6

  • Online ISBN: 978-3-642-17563-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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