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Analysis on a Multi-objective Binary Disperse Bacterial Colony Chemotaxis Algorithm and Its Convergence

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Advances in Swarm Intelligence (ICSI 2014)

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Abstract

A simple, convenient and efficient multi-objective binary disperse optimized bacterial colony chemotaxis algorithm (MDOBCC) is proposed, in which the Disp(disperse update mechanism) is defined to handle 0-1 disperse optimization problems. The concept of chemotaxis center is proposed with the item of group and chemotaxis in order to improve the convergence rate of the algorithm. The definition of reference colony is used to retain the elite solution produced during the iteration; the definition of colony spatial radius and density is used to guide the bacteria for determinate variation, thus keeping the algorithm obtain even-distributed Pareto optimum solution set. Furthermore, the derivation analysis is given to prove the convergence of the algorithm and comes to the conclusion of global convergence. The simulate result confirmed the effectiveness of the algorithm.

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Feng, T., Liu, Z., Lu, Z. (2014). Analysis on a Multi-objective Binary Disperse Bacterial Colony Chemotaxis Algorithm and Its Convergence. 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_43

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  • DOI: https://doi.org/10.1007/978-3-319-11857-4_43

  • 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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