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A Differentiating Evolutionary Computation Approach for the Multidimensional Knapsack Problem

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7331))

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Abstract

In this paper, the DEC (Differentiating Evolutionary Computation) algorithm is presented for solving a zero-one multidimensional knapsack problem. It has three new improvements. They are the use of a chromosome bank for elitism, the use of the superior clan and the inferior clan to improve exploitation and exploration, and the use of genetic modification to enable faster convergence. The experimental results have shown that the DEC algorithm is better than a greedy algorithm and a generic genetic algorithm. It can find solutions very close to those found by the algorithm proposed by Chu & Beasley.

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References

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Author information

Authors and Affiliations

  1. Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, 63100, Cyberjaya, Malaysia

    Meysam Mohagheghi Fard, Yoon-Teck Bau & Chien-Le Goh

Authors
  1. Meysam Mohagheghi Fard
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  2. Yoon-Teck Bau
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  3. Chien-Le Goh
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

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

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Fard, M.M., Bau, YT., Goh, CL. (2012). A Differentiating Evolutionary Computation Approach for the Multidimensional Knapsack Problem. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_41

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  • DOI: https://doi.org/10.1007/978-3-642-30976-2_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30975-5

  • Online ISBN: 978-3-642-30976-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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