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Modeling and solving simultaneous delivery and pick-up problem with stochastic travel and service times in home health care

机译:建模和解决家庭保健中具有随机旅行和服务时间的同时分娩和接送问题

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Home Health Care (HHC) companies are widespread in European countries and aim to serve patients at home to help them recover from illness and injury in a personal environment. Since transportation costs constitute one of the largest forms of expenditure in the HHC industry, it is of importance to research the optimization of the HHC logistics. This paper considers an HHC routing problem with stochastic travel and service times, which comes from the logistics practice of HHC companies. A Stochastic Programming model with Recourse (SPR model) is proposed based on the specific structure of the supply chain. Three series of experiments are carried out to evaluate the model. Firstly, the SPR model is reduced to the deterministic one, and five approaches (Gurobi Solver, Hybrid Genetic Algorithm, Simulated Annealing, Bat Algorithm and Firefly Algorithm) are respectively implemented to solve the deterministic model. The SPR model is finally solved by the proposed SA-based heuristic algorithm. Evaluation of the solutions achieved by the two models highlights the advantages of considering stochastic travel and service times. Finally, a case study is given to explain how the SPR model works for an HHC company. This research will help HHC companies to make appropriate decisions when planning their vehicle routes. (C) 2018 Elsevier Ltd. All rights reserved.
机译:家庭保健(HHC)公司在欧洲国家中广泛存在,旨在为患者提供在家中服务,以帮助他们在个人环境中从疾病和受伤中康复。由于运输成本是HHC行业最大的支出形式之一,因此研究HHC物流的优化至关重要。本文考虑具有随机旅行和服务时间的HHC路由问题,该问题来自HHC公司的物流实践。基于供应链的具体结构,提出了带资源的随机规划模型(SPR模型)。进行了三个系列的实验来评估模型。首先,将SPR模型简化为确定性模型,并分别采用五种方法(Gurobi求解器,混合遗传算法,模拟退火,蝙蝠算法和萤火虫算法)求解确定性模型。最终,所提出的基于SA的启发式算法解决了SPR模型。对这两个模型实现的解决方案的评估突出了考虑随机旅行和服务时间的优势。最后,通过一个案例研究来说明SPR模型如何用于HHC公司。这项研究将帮助HHC公司在规划车辆路线时做出适当的决定。 (C)2018 Elsevier Ltd.保留所有权利。

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