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Multicriteria tour planning for mobile healthcare facilities in a developing country

机译:发展中国家移动医疗设施的多标准旅游计划

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摘要

A multiobjective combinatorial optimization (MOCO) formulation for the following location-routing problem in healthcare management is given: For a mobile healthcare facility, a closed tour with stops selected from a given set of population nodes has to be found. Tours are evaluated according to three criteria: (i) An economic efficiency criterion related to the tour length, (ii) the criterion of average distances to the nearest tour stops corresponding to p-median location problem formulations, and (iii) a coverage criterion measuring the percentage of the population unable to reach a tour stop within a predefined maximum distance. Three algorithms to compute approximations to the set of Pareto-efficient solutions of the described MOCO problem are developed. The first uses the P-ACO technique, and the second and the third use the VEGA and the MOGA variant of multiobjective genetic algorithms, respectively. Computational experiments for the Thies region in Senegal were carried out to evaluate the three approaches on real-world problem instances. (c) 2006 Elsevier B.V. All rights reserved.
机译:针对医疗保健管理中的以下选路问题,给出了一种多目标组合优化(MOCO)公式:对于移动医疗保健机构,必须找到一个从给定的人口节点集中选择停靠点的封闭游览。根据三个标准对旅行进行评估:(i)与旅行长度相关的经济效率标准;(ii)对应于p中位数位置问题公式的到最近旅行站点的平均距离标准;以及(iii)覆盖标准测量无法在预定义的最大距离内到达游览站点的人口百分比。开发了三种算法来计算所描述的MOCO问题的帕累托有效解的近似值。第一种使用P-ACO技术,第二种和第三种分别使用多目标遗传算法的VEGA和MOGA变体。进行了塞内加尔Thies地区的计算实验,以评估在实际问题实例上的三种方法。 (c)2006 Elsevier B.V.保留所有权利。

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