一种用于提供紧急医疗服务的稳健双目标定位路由模型

IF 3.2 Q2 MANAGEMENT
Hesam Adarang, A. Bozorgi-Amiri, K. Khalili-Damghani, R. Tavakkoli-Moghaddam
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引用次数: 18

摘要

目的利用鲁棒优化(RO)方法,研究灾害中紧急医疗服务(EMS)在不确定条件下的位置-路由问题(LRP)。目标包括尽量减少救济时间和总费用,包括地点费用和车辆(救护车和直升机)覆盖路线的费用。为解决这一问题,提出了一种shuffle frog leapalgorithm (SFLA),并采用ε-约束方法和NSGA-II算法对其性能进行了评估。为了更准确地验证所提出的算法,使用了分散测度(DM)、平均理想距离(MID)、空间测度(SM)和帕累托解数(NPS)四个指标。结果表明,与CPLEX求解器相比,该算法在适当的计算时间内具有较高的效率。研究局限/启示在本研究中,模型并未考虑规划视界对需求等参数值的影响。此外,该模型未考虑其他参数(如行驶时间)的不确定性。实际意义本研究结果可为决策者在不确定环境下的伤亡运输规划与管理提供参考。所提出的算法可以得到真实情况下可接受的解。提出了一种新的鲁棒混合整数线性规划(MILP)模型,将该问题表述为LRP问题。为了解决这一问题,提出了两种高效的元启发式算法来确定目标和决策变量的最优值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust bi-objective location-routing model for providing emergency medical services
PurposeThis paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters).Design/methodology/approachA shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used.FindingsThe results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method.Research limitations/implicationsIn this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model.Practical implicationsThe outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases.Originality/valueA novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.
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来源期刊
CiteScore
6.40
自引率
20.00%
发文量
20
期刊介绍: The Journal of Humanitarian Logistics and Supply Chain Management (JHLSCM) is targeted at academics and practitioners in humanitarian public and private sector organizations working on all aspects of humanitarian logistics and supply chain management. The journal promotes the exchange of knowledge, experience and new ideas between researchers and practitioners and encourages a multi-disciplinary and cross-functional approach to the resolution of problems and exploitations of opportunities within humanitarian supply chains. Contributions are encouraged from diverse disciplines (logistics, operations management, process engineering, health care, geography, management science, information technology, ethics, corporate social responsibility, disaster management, development aid, public policy) but need to have a logistics and/or supply chain focus. JHLSCM publishes state of the art research, utilizing both quantitative and qualitative approaches, in the field of humanitarian and development aid logistics and supply chain management.
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