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A Hybrid Algorithm Based on Tabu Search and Chemical Reaction Optimization for 0-1 Knapsack Problem

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Advances in Swarm and Computational Intelligence (ICSI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9141))

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Abstract

The 0-1 knapsack problem(01KP) is a well-known NP-complete problem in combinatorial optimization problems. There exist different approaches employed to solve the problem such as brute force, dynamic programming, branch and bound, etc. In this paper, a hybrid algorithm CROTS (Chemical Reaction Optimization combined with Tabu Search) is proposed to address the issue. One of the four elementary reaction of CRO is performed first, and after that tabu search is employed to search for the neighbors of the optimum solution in the population. The experimental results show that CROTS owns better performance in comparison with GA and the original CRO.

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References

  1. Lam, A.Y.S., Li, V.O.K.: Chemical Reaction Optimization: a tutorial. Memetic Computing 4(1), 3–17 (2012)

    Article  Google Scholar 

  2. Mohamed Esseghir, L., Didier, E.-B.: GPU implementation of the branch and bound method for knapsack problems. In: IEEE International Symposium on Parallel and Distributed Processing Workshops and Ph.D Forum-IPDPSW, pp. 1769–1777 (2012)

    Google Scholar 

  3. Ben-Romdhane, H., Ben Jouida, S., Krichen, S.: A dynamic approach for the online knapsack problem. In: Torra, V., Narukawa, Y., Endo, Y. (eds.) MDAI 2014. LNCS, vol. 8825, pp. 96–107. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  4. George, M., Jose Rui, F., Kostas, F.: Solving the bi-objective multi-dimensional knapsack problem exploiting the concept of core. Applied Mathematics and Computation 215(7), 2502–2514 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  5. Leung, S.C.H., Zhang, D.F.: A hybrid simulated annealing metaheuristic algorithm for the two-dimensional knapsack packing problem. Computers & Operations Research 39(1), 64–73 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  6. Lai, G.M., Yuan, D.H.: A new hybrid combinatorial genetic algorithm for multidimensional knapsack problems. Journal of Supercomputing 70(2), 930–945 (2014)

    Article  Google Scholar 

  7. Shen, W., Xu, B.: An Improved Genetic Algorithm for 0-1 Knapsack Problems. In: 2011 Second International Conference on Networking and Distributed Computing (ICNDC), pp. 32–35 (2011)

    Google Scholar 

  8. Han, K.-H., Kim, J.-H.: Quantum-Inspired Evolutionary Algorithm for a Class of Combinatorial Optimization. IEEE Transactions on Evolutionary Computation 6(6), 580–593 (2002)

    Article  Google Scholar 

  9. Truong, T.K., Li, K.: Chemical reaction optimization with greedy strategy for the 0–1 knapsack problem. Applied Soft Computing 13(4), 1774–1780 (2013)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Computer and Information Engineering, Henan University, Kaifeng, China

    Chaokun Yan, Siqi Gao & Huimin Luo

  2. School of Information Science and Engineering, Central South University, Changsha, China

    Huimin Luo & Zhigang Hu

Authors
  1. Chaokun Yan
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  2. Siqi Gao
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  3. Huimin Luo
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  4. Zhigang Hu
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Corresponding author

Correspondence to Huimin Luo .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'ian Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Universidade de Pernambuco, Recife, Brazil

    Fernando Buarque

  4. Instituto Politécnico Nacional, Mexico, Mexico

    Alexander Gelbukh

  5. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  6. University of Pretoria, Pretoria, South Africa

    Andries Engelbrecht

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Yan, C., Gao, S., Luo, H., Hu, Z. (2015). A Hybrid Algorithm Based on Tabu Search and Chemical Reaction Optimization for 0-1 Knapsack Problem. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9141. Springer, Cham. https://doi.org/10.1007/978-3-319-20472-7_25

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  • DOI: https://doi.org/10.1007/978-3-319-20472-7_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20471-0

  • Online ISBN: 978-3-319-20472-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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