Robust homecare service capacity planning

作     者：Xie, Weiping Liu, Tianqi Li, Xiang Zheng, Chenyang 

作者机构：Case Western Reserve Univ Dept Math Appl Math & Stat Cleveland OH USA Capital Univ Econ & Business Sch Management & Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing Peoples R China Univ Wisconsin Madison Dept Ind & Syst Engn Madison WI USA 

出 版 物：《COMPUTERS & OPERATIONS RESEARCH》 (计算机与运筹学研究)

年 卷 期：2023年第154卷第1期

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China (NNSFC) [71922020, 72171221] NNSFC, China 

主　　题：Home health care Linear programming Adaptive robust optimization Benders decomposition 

摘      要：We study a home healthcare planning problem under the demand uncertainty, where the service type (authorization) and capacity are the first-stage decision and the homecare resource allocation is the second -stage decision which adapts to the demand realizations. We model the problem using an adaptive robust optimization technique where we construct a budget uncertainty set of demand using the well-known Mahalanobis Distance. We analyze the impact of the authorization, capacity decisions as well as the budget (robustness level) of the Mahalanobis uncertainty set onto the worst-case revenue. To solve the model, we develop a Benders decomposition algorithm that solves a pair of a mixed-integer second-order cone program (MISOCP) and a mixed integer linear program (MILP) in each iteration, both can be handled by off-the-shelf MIP solvers, with finite-step convergence. We also develop an affine approximation approach that directly solves one instance of MISOCP. Finally, sufficient numerical studies demonstrate the effectiveness of our model and the solution approaches.