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Monte Carlo Method for Multiple Knapsack Problem

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Large-Scale Scientific Computing (LSSC 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2907))

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Abstract

This paper describes Monte Carlo (MC) method for Multiple Knapsack Problem (MKP). The MKP can be defined as economical problem like resource allocation and capital budgeting problems. The Ant Colony Optimization (ACO) is a MC method, created to solve Combinatorial Optimization Problems (COPs). The paper proposes a Local Search (LC) procedure which can be coupled with the ACO algorithm to improve the efficiency of the solving of the MKP. This will provide optimal or near optimal solutions for large problems with an acceptable amount of computational effort. Computational results have been presented to assess the performance of the proposed technique.

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© 2004 Springer-Verlag Berlin Heidelberg

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Fidanova, S. (2004). Monte Carlo Method for Multiple Knapsack Problem. In: Lirkov, I., Margenov, S., Waśniewski, J., Yalamov, P. (eds) Large-Scale Scientific Computing. LSSC 2003. Lecture Notes in Computer Science, vol 2907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24588-9_14

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  • DOI: https://doi.org/10.1007/978-3-540-24588-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21090-0

  • Online ISBN: 978-3-540-24588-9

  • eBook Packages: Springer Book Archive

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