Customization of PSO Algorithm for Fast Design of Emergency Medical System

Marek Kvet, J. Janáček
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Abstract

Mathematical modelling, and integer programming generally, has many practical applications in the field of emergency system designing. Effective and fast solving approaches for real-sized problems constitute a key stone of the decision support systems. This paper is focused only on a special class of location problems in which the exact number of facilities are to be selected in order to minimize average response time of the emergency medical system. Since the exact methods are not suitable for their unpredictable computational time, we focus on usage of a special type of a particle swarm optimization algorithm transformed to a discrete mode. We aim at the goal to confirm the hypothesis that it is possible to suggest a sophisticated heuristic for the problem, which can produce a near-to-optimal solution in much smaller time than demanded by exact methods. Especially, we concentrate our effort on customization of the algorithm by usage of uniformly deployed set as a starting swarm and on determining its most convenient size. To verify the impact of the customization, computational study with real-sized benchmarks was performed.
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面向应急医疗系统快速设计的粒子群算法定制
数学建模和一般的整数规划在应急系统设计领域有许多实际应用。有效、快速地解决实际问题的方法是决策支持系统的关键。本文只关注一类特殊的选址问题,在这类选址问题中,为了最小化应急医疗系统的平均响应时间,需要选择准确的设施数量。由于精确方法不适合其不可预测的计算时间,我们着重于使用一种特殊类型的转化为离散模式的粒子群优化算法。我们的目标是确认这样一个假设,即有可能为这个问题提出一个复杂的启发式方法,它可以在比精确方法所需的更短的时间内产生接近最优的解决方案。特别是,我们集中精力通过使用统一部署的集合作为起始群来定制算法,并确定其最方便的大小。为了验证定制的影响,使用实际尺寸的基准进行了计算研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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