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A New Hybrid Algorithm for the Multidimensional Knapsack Problem

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Bio-Inspired Computing and Applications (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

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Abstract

This paper presents a novel hybrid algorithm to solve the multidimensional knapsack problem. The main feature of this hybrid algorithm is to combine the solution construction mechanism of ant colony optimization (ACO) into scatter search (SS). It considers both solution quality and diversification. A new mechanism of the subset combination method has been applied simultaneity, which hybridizes mechanism of the pheromone trail updating with combination mechanism of scatter search to generate new solutions. Second, an improvement algorithm should be embedded into the scatter search framework to improve solutions. Finally, the experimental results have shown that our proposed method is competitive to solve the multidimensional knapsack problem compared with the other heuristic methods in terms of solution quality.

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References

  1. Gilmore, P.C., Gomory, R.E.: The theory and computation of knapsack functions. Operations Research 14, 1045–1075 (1966)

    Article  MathSciNet  MATH  Google Scholar 

  2. Beaujon, G.J., Martin, S.P., McDonald, C.C.: Balancing and optimizing a portfolio of R&D projects. Naval Research Logistics 4818–4840 (2001)

    Google Scholar 

  3. Gavish, B., Pirkul, H.: Allocation of databases and processors in a distributed data processing. In: Akola, J. (ed.) Management of Distributed Data Processing, pp. 215–231. North-Holland, Amsterdam (1982)

    Google Scholar 

  4. Drexl, A.: A simulated annealing approach to the multiconstraint zero–one knapsack problem. Computing 40, 1–8 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  5. Dammeyer, F., Voss, S.: Application of tabu search strategies for solving multiconstraint zero–one knapsack problems. In: Working Paper, Technische Hochschule Darmstadt, Germany (1991)

    Google Scholar 

  6. Battiti, R., Tecchiolli, G.: The reactive tabu search. ORSA Journal on Computing 6, 126–140 (1994)

    Article  MATH  Google Scholar 

  7. Thiel, J., Voss, S.: Some experiences on solving multiconstraint zero–one knapsack problems with genetic algorithms. INFOR 32, 226–242 (1994)

    MATH  Google Scholar 

  8. Chu, P., Beasley, J.: A genetic algorithm for the multidimensional knapsack problem. Journal of Heuristics 4, 63–86 (1998)

    Article  MATH  Google Scholar 

  9. Dorigo, M., Gambardella, L.M.: Ant colonies for the traveling salesman problem. BioSystems 43, 73–81 (1997)

    Article  Google Scholar 

  10. Leguizamon, G., Michalewicz, Z.: A new version of ant system for subset problem. In: Congress on Evolutionary Computation, pp. 1456–1464 (1999)

    Google Scholar 

  11. Glover, F.: Heuristics for integer programming using surrogate constraints. Decision Sciences, 8156–8166 (1977)

    Google Scholar 

  12. Bell, J.E., McMullen, P.R.: Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics 18, 41–48 (2004)

    Article  Google Scholar 

  13. Russell, R.A., Chiang, W.C.: Scatter search for the vehicle routing problem with time windows. European Journal of Operational Research 169, 606–622 (2006)

    Google Scholar 

  14. Marti, M., Laguna, M., Glover, F.: Principles of scatter search. European Journal of Operational Research 169, 359–372 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  15. Magazine, M.J., Oguz, O.: A heuristic algorithm for the multidimensional zero-one Knapsack Problem. European Journal of Operational Research 16, 319–326 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  16. Volgenant, A., Zoon, J.A.: An improved heuristic for multidimensional 0-1 knapsack problems. Journal of the Operational Research Society 41, 963–970 (1990)

    Article  MATH  Google Scholar 

  17. Pirkul, H.: A heuristic solution procedure for the multiconstraint zero-one knapsack problem. Naval Research Logistics 34, 161–172 (1987)

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Software Engineering, University of Science and Technology, Liaoning, China

    Xiaoxia Zhang, Zhe Liu & Qiuying Bai

Authors
  1. Xiaoxia Zhang
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  2. Zhe Liu
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  3. Qiuying Bai
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, 2522, P.O. Box, North Wollongong, NSW, Australia

    Prashan Premaratne

  4. School of Computer Science and Engineering, Inha University, 402-751, Inchon, Korea

    Kyungsook Han

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhang, X., Liu, Z., Bai, Q. (2012). A New Hybrid Algorithm for the Multidimensional Knapsack Problem. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_27

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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