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A Multi-objective Jumping Particle Swarm Optimization Algorithm for the Multicast Routing

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Advances in Swarm Intelligence (ICSI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8794))

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Abstract

This paper presents a new multi-objective jumping particle swarm optimization (MOJPSO) algorithm to solve the multi-objective multicast routing problem, which is a well-known NP-hard problem in communication networks. Each particle in the proposed MOJPSO algorithm performs four jumps, i.e. the inertial, cognitive, social and global jumps, in such a way, particles in the swarm follow a guiding particle to move to better positions in the search space. In order to rank the non-dominated solutions obtained to select the best guider of the particle, three different ranking methods, i.e. the random ranking, an entropy-based density ranking, and a fuzzy cardinal priority ranking are investigated in the paper. Experimental results show that MOJPSO is more flexible and effective for exploring the search space to find more non-dominated solutions in the Pareto Front. It has better performance compared with the conventional multi-objective evolutionary algorithm in the literature.

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Author information

Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, Hunan, P.R. China

    Ying Xu

  2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031, Sichuan, P.R. China

    Huanlai Xing

Authors
  1. Ying Xu
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  2. Huanlai Xing
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Computer Science Department, CINVESTAV-IPN, Mexico

    Carlos A. Coello Coello

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Xu, Y., Xing, H. (2014). A Multi-objective Jumping Particle Swarm Optimization Algorithm for the Multicast Routing. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8794. Springer, Cham. https://doi.org/10.1007/978-3-319-11857-4_47

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  • DOI: https://doi.org/10.1007/978-3-319-11857-4_47

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11856-7

  • Online ISBN: 978-3-319-11857-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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