具有动态休息时间的双目标家庭护理调度问题
A biobjective Home Care Scheduling Problem with dynamic breaks
AI总结：
本文研究西班牙家庭护理公司的双目标调度问题，旨在平衡用户福利与调度成本，提出基于MDLS的定制元启发式算法，通过实验验证其优于AUGMECON2和NSGA-II算法，并成功应用于实际实例。
摘要：
本文提出了一个多目标家庭护理调度问题（以下简称 multiobjective HCSP），与位于西班牙北部的一家老年人和依赖性人群家庭护理公司相关。具体而言，考虑了一个双目标问题，包含以下两个冲突的目标：用户的福利和调度的成本。为了解决该问题，设计了一种基于多方向局部搜索（MDLS）的定制元启发式算法，在高效的计算时间内获得了 Pareto 前沿的良好近似。该双目标算法可分为三个步骤：初始化非支配解集、生成由不同路径组成的解以及获取非支配解。通过实现文献中另外两种著名方法来分析该双目标算法的性能：精确方法 AUGMECON2（仅是 Epsilon Constraint 方法的改进版本）和基于 NSGA-II 的算法。最后，进行了一项广泛的计算研究，在文献中的一组实例上比较了这三种方法，其中双目标算法表现出优越的性能。此外，该算法还应用于实际实例，为公司提供了在两个目标之间具有良好权衡的解决方案。
英文摘要：
This paper presents a multiobjective Home Care Scheduling Problem (from now on multiobjective HCSP) related to a home care company for elderly and dependent people located in the North of Spain. In particular, a biobjective problem is considered, with the following two conflicting objectives: the welfare of users and the cost of schedules. To tackle the problem, a custom metaheuristic algorithm based on the Multi-Directional Local Search (MDLS) was designed, obtaining good approximations of the Pareto frontier in efficient computational times. This biobjective algorithm can be divided into three steps: initializing the set of non dominated solutions, generating solutions composed by different routes and obtaining non dominated solutions. The performance of the biobjective algorithm was analyzed by implementing two other well known methods in the literature: the exact method AUGMECON2, which is just an improved version of the Epsilon Constraint approach, and an NSGA-II-based algorithm. Finally, an extensive computational study was developed to compare the three methods over a set of instances from the literature, where the biobjective algorithm exhibited a superior behaviour. Furthermore, the algorithm was also applied to real instances providing solutions to the company with a good trade-off between the two objectives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
