Citations per year

202220232024124
Abstract: (arXiv)
Optimization problems is one of the most challenging applications of quantum computers, as well as one of the most relevants. As a consequence, it has attracted huge efforts to obtain a speedup over classical algorithms using quantum resources. Up to now, many problems of different nature have been addressed through the perspective of this revolutionary computation paradigm, but there are still many open questions. In this work, a hybrid classical-quantum approach is presented for dealing with the one-dimensional Bin Packing Problem (1dBPP). The algorithm comprises two modules, each one designed for being executed in different computational ecosystems. First, a quantum subroutine seeks a set of feasible bin configurations of the problem at hand. Secondly, a classical computation subroutine builds complete solutions to the problem from the subsets given by the quantum subroutine. Being a hybrid solver, we have called our method H-BPP. To test our algorithm, we have built 18 different 1dBPP instances as a benchmarking set, in which we analyse the fitness, the number of solutions and the performance of the QC subroutine. Based on these figures of merit we verify that H-BPP is a valid technique to address the 1dBPP.
Note:
  • 10 pages, 2 figures, 3 tables, submitted to the Genetic and Evolutionary Computation Conference 2022 (GECCO 2022)
  • [1]

  • [2]

    Quantum computing based hybrid solution strategies for large-scale discrete-continuous optimization problems

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  • [3]

    A study and analysis of applications of classical computing and quantum computing: A survey

    • A. Navaneeth
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  • [4]

    A survey and tutorial on security and resilience of quantum computing

    • A.A. Saki
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    European Test Symposium (ETS)
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    • R.O. Topaloglu
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    A survey of quantum computing for finance

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    Limitations in quantum computing from resource constraints

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    Natural limitations of quantum computing

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      • Evol.Comput. 6 (2017) 2
  • [8]

    Approximation algorithms for bin packing problems: A survey

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    • D.S. Johnson
  • [9]

    Metaheuristic approaches for one-dimensional bin packing problem: A comparative performance study

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    et al.
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  • [10]

    Adiabatic quantum optimization fails to solve the knapsack problem

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  • [11]

    Improved classical and quantum algorithms for subset-sum

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  • [12]

    Bin packing problem with time dimension: An application in cloud computing

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  • [13]

    Multi-objective temporal bin packing problem: An application in cloud computing

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  • [14]

    A fast quantum mechanical algorithm for database search

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  • [15]

    Algorithms for quantum computation: discrete logarithms and factoring

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  • [16]

    Bqp and the polynomial hierarchy

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  • [18]

    Limitations of optimization algorithms on noisy quantum devices

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  • [20]

    Some optimal inapproximability results

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  • [21]

    A polynomial time bounded-error quantum algorithm for boolean satisfiability

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    • J.E. Rowe
  • [22]

    Quantum computational networks

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  • [23]

    What is a quantum simulator?

    • T.H. Johnson
      ,
    • S.R. Clark
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    • D. Jaksch
      • EPJ Quant.Technol. 1 (2014) 10