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A quantum particle swarm optimization for the 0–1 generalized knapsack sharing problem

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Abstract

This study proposes a new hybrid heuristic approach that combines the quantum particle swarm optimization (QPSO) technique with a local search phase to solve the binary generalized knapsack sharing problem (GKSP). The approach also incorporates a heuristic repair operator that uses problem-specific knowledge instead of the penalty function technique commonly used for constrained problems. This study is the first to report on the application of the QPSO method to the GKSP. The efficiency of our proposed approach was tested on a large set of instances, and the results were compared to those produced by the commercial mixed integer programming solver CPLEX 12.5 of IBM-ILOG. The Experimental results demonstrated the good performance of the QPSO in solving the GKSP.

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References

  • Abraham A, Guo H, Liu H (2006) Swarm intelligence: foundations, perspectives and applications. Springer, New York

    Google Scholar 

  • Brotcorne L, Laporte G, Semet F (2003) Ambulance location and relocation models. Eur J Oper Res 147(3):451–463

    Article  MathSciNet  MATH  Google Scholar 

  • Clerc M (2006) Particle swarm optimization. ISTE Publishing Company, London

    Book  MATH  Google Scholar 

  • Engelbrecht AP (2005) Fundamentals of computational swarm intelligence. Wiley, Hoboken

    Google Scholar 

  • Fujimoto M, Yamada T (2006) An exact algorithm for the knapsack sharing problem with common items. Eur J Oper Res 171(2):693–707

    Article  MathSciNet  MATH  Google Scholar 

  • Hanafi S, Wilbaut C (2011) Improved convergent heuristics for the 0–1 multidimensional knapsack problem. Ann Oper Res 183(1):125–142

    Article  MathSciNet  MATH  Google Scholar 

  • Hey T (1999) Quantum computing: an introduction. Comput Control Eng J 10(3):105–112

    Article  Google Scholar 

  • Horowitz E, Sahni S (1974) Computing partitions with applications to the knapsack problem. J ACM 21(2):277–292

    Article  MathSciNet  MATH  Google Scholar 

  • Kennedy J (1999) Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. In: Proceedings of the 1999 congress on evolutionary computation, 1999, CEC 99, vol 3

  • Kennedy J (2000) Stereotyping: improving particle swarm performance with cluster analysis. In: Proceedings of the 2000 congress on evolutionary computation, vol 2, pp 1507–1512

  • Kennedy J (2003) Bare bones particle swarms. In: Proceedings of the 2003 swarm intelligence symposium, IEEE, pp 80–87

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of the 1995 IEEE international conference on neural networks, vol 4, pp 1942–1948

  • Kennedy J, Eberhart R (1997) A discrete binary version of the particle swarm algorithm. In: Proceedings of the 1997 IEEE international conference on computational cybernetics and simulation, vol 5, pp 4104–4108

  • Khanesar MA, Teshnehlab M, Shoorehdeli MA (2007) A novel binary particle swarm optimization. In: Mediterranean conference on control & automation, 2007, MED’07, IEEE, pp 1–6.

  • Krohling RA, dos Santos Coelho L (2006) PSO-E: Particle swarm with exponential distribution. In: IEEE congress on evolutionary computation, CEC 2006, pp 1428–1433

  • Langeveld J, Engelbrecht AP (2012) Set-based particle swarm optimization applied to the multidimensional knapsack problem. Swarm Intell 6(4):297–342

    Article  Google Scholar 

  • Martello S, Toth P (1990) Knapsack problems: algorithms and computer implementations. Wiley, New York

    MATH  Google Scholar 

  • Martello S, Toth P (1997) Upper bounds and algorithms for hard 0–1 knapsack problems. Oper Res 45(5):768–778

    Article  MathSciNet  MATH  Google Scholar 

  • Mohais A, Mendes R, Ward C, Posthoff C (2005) Neighborhood restructuring in particle swarm optimization. In: Proceedings of the 2005 advances in artificial intelligence. Lecture notes in computer science, vol 3809. Springer, Berlin, pp 776–785

  • Nezamabadi-pour H, Rostami Shahrbabaki M, Maghfoori-Farsangi M (2008) Binary particle swarm optimization: challenges and new solutions. CSI J Comput Sci Eng 6(1):21–32 (in Persian)

    Google Scholar 

  • Pampara G, Franken N, Engelbrecht AP (2005) Combining particle swarm optimisation with angle modulation to solve binary problems. In: IEEE Congress on evolutionary computation, 2005, vol 1, pp 89–96

  • Parrott D, Li X (2006) Locating and tracking multiple dynamic optima by a particle swarm model using speciation. IEEE Trans Evolut Comput 10(4):440–458

    Article  Google Scholar 

  • Soyster AL, Lev B, Slivka W (1978) Zero-one programming with many variables and few constraints. Eur J Oper Res 2(3):195–201

    Article  MATH  Google Scholar 

  • Sun J, Feng B, Xu W (2004a) Particle swarm optimization with particles having quantum behavior. In: Proceedings of the 2004 congress on evolutionary computation, vol 1, pp 325–331

  • Sun J, Xu W, Feng B (2004b) A global search strategy of quantum-behaved particle swarm optimization. In: Proceedings of the 2004 IEEE conference on cybernetics and intelligent systems, vol 1, pp 111–116

  • Vasseur JP, Pickavet M, Demeester P (2004) Network recovery: protection and restoration of optical. SONET-SDH, IP, and MPLS. Elsevier, New York

  • Yamada T, Futakawa M, Kataoka S (1998) Some exact algorithms for the knapsack sharing problem. Eur J Oper Res 106(1):177–183

    Article  Google Scholar 

  • Yang S, Wang M, Jiao L (2004) A quantum particle swarm optimization. In: Proceedings of the 2004 congress IEEE conference on evolutionary computation, vol 1, pp 320–324

Download references

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Correspondence to Mahdi Khemakhem.

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Haddar, B., Khemakhem, M., Rhimi, H. et al. A quantum particle swarm optimization for the 0–1 generalized knapsack sharing problem. Nat Comput 15, 153–164 (2016). https://doi.org/10.1007/s11047-014-9470-5

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