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Multiobjective 0/1 Knapsack Problem using Adaptive ε-Dominance

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Applied Soft Computing Technologies: The Challenge of Complexity

Part of the book series: Advances in Soft Computing ((AINSC,volume 34))

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Abstract

The multiobjective 0/1 knapsack problem is a generalization of the well known 0/1 knapsack problem in which multiple knapsacks are considered. A new evolutionary algorithm for solving multiobjective 0/1 knapsack problem is proposed in this paper. This algorithm used a ε-dominance relation for direct comparison of two solutions. This algorithm try to improve another algorithm which also uses an ε domination relation between solutions. In this new algorithm the value of ε is adaptive (can be changed) depending on the solutions quality improvement. Several numerical experiments are performed using the best recent algorithms proposed for this problem. Experimental results clearly show that the proposed algorithm outperforms the existing evolutionary approaches for this problem.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Babeş-Bolyai University, Kogăalniceanu 1, Cluj-Napoca, 3400, Romania

    Crina Groşan

Authors
  1. Crina Groşan
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Chung-Ang University, Heukseok-dong 221, 156-756, Seoul, Korea

    Ajith Abraham

  2. Department of Applied Mathematics Biometrics and Process Control, University Gent, Coupure Links 653, 9000 Gent, Belgium

    Bernard de Baets

  3. Dept. Automation Technologies, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  4. Dept. Automation Technologies, Fraunhofer IPK Berlin, Pascalstr. 8-9, 10587, Berlin, Germany

    Bertram Nickolay

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© 2006 Springer

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Groşan, C. (2006). Multiobjective 0/1 Knapsack Problem using Adaptive ε-Dominance. In: Abraham, A., de Baets, B., Köppen, M., Nickolay, B. (eds) Applied Soft Computing Technologies: The Challenge of Complexity. Advances in Soft Computing, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31662-0_42

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  • DOI: https://doi.org/10.1007/3-540-31662-0_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31649-7

  • Online ISBN: 978-3-540-31662-6

  • eBook Packages: EngineeringEngineering (R0)

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