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Author:

Wei, Hongkai (Wei, Hongkai.) | Ji, Junzhong (Ji, Junzhong.) (Scholars:冀俊忠) | Qin, Yufang (Qin, Yufang.) | Wang, Yamin (Wang, Yamin.) | Liu, Chunnian (Liu, Chunnian.)

Indexed by:

CPCI-S EI Scopus

Abstract:

In this paper, we propose a novel artificial bee colony(ABC) algorithm for the multidimensional knapsack problems, which introduces the attraction pheromone and presents a transition strategy based on the attraction pheromone. In our algorithm, the scout generates a food source according to the transition strategy and replaces the abandoned food source by comparison with the corresponding elite food source, while the employed bee and onlooker modify the repair operator using the transition strategy in the determination of the neighborhood of a food source. Experimental results show that our approach performs better in the quality of solutions, the convergence speed and the time performance than traditional ABC algorithm.

Keyword:

Artificial bee colony algorithm multidimensional knapsack problems attraction pheromone transition strategy

Author Community:

  • [ 1 ] [Wei, Hongkai]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing 100124, Peoples R China
  • [ 2 ] [Ji, Junzhong]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing 100124, Peoples R China
  • [ 3 ] [Qin, Yufang]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing 100124, Peoples R China
  • [ 4 ] [Liu, Chunnian]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing 100124, Peoples R China
  • [ 5 ] [Wang, Yamin]Liaocheng Univ, Coll Comp Sci, Liaocheng 252059, Peoples R China

Reprint Author's Address:

  • [Wei, Hongkai]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing 100124, Peoples R China

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Source :

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PT II

ISSN: 0302-9743

Year: 2011

Volume: 7003

Page: 1-,

Language: English

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 14

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