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Quantum binary particle swarm optimization-based algorithm for solving a class of bi-level competitive facility location problems

机译：基于量子二进制粒子群算法的一类双水平竞争性设施选址算法

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This paper deals with a special class of competitive facility location problems, in which two non-cooperative firms compete to capture the most of a given market, in order to maximize their profit. This paper intends to present a simple and effective nested strategy based on the quantum binary particle swarm optimization (QBPSO) method for solving the bi-level mathematical model of the problem. In solution approach, an improvement procedure is embedded into QBPSO to increase the convergence speed and generate more accurate solutions. Taguchi's method is employed to systematically determine the optimal values of QBPSO parameters. Finally, computational results on large-scale instances with up to 300 locations and 350 clients (more than 100,000 variables and 300,000 constraints at each level) confirmed the method efficiency in terms of solution quality and time.
机译：本文涉及一类特殊的竞争性设施选址问题，其中两个非合作公司竞争以占领给定市场的大部分，以最大程度地提高利润。本文旨在提出一种基于量子二进制粒子群优化（QBPSO）方法的简单有效的嵌套策略，用于求解该问题的双层数学模型。在解决方案方法中，将改进过程嵌入QBPSO中，以提高收敛速度并生成更准确的解决方案。 Taguchi方法被用来系统地确定QBPSO参数的最佳值。最后，在多达300个位置和350个客户端（每个级别有100,000多个变量和300,000个约束）的大型实例上的计算结果证实了该方法在解决方案质量和时间方面的效率。

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