Integration routing and scheduling for multiple home health care centers using a multi-objective cooperation evolutionary algorithm with stochastic simulation

被引:30
|
作者
Ma, Xiaomeng [1 ]
Fu, Yaping [1 ]
Gao, Kaizhou [2 ,3 ]
Sadollah, Ali [4 ]
Wang, Kai [1 ]
机构
[1] Qingdao Univ, Sch Business, Qingdao 266071, Peoples R China
[2] Macau Univ Sci & Technol, Inst Syst Engn, Taipa 999078, Macau, Peoples R China
[3] Macau Univ Sci & Technol, Collaborat Lab Intelligent Sci & Syst, Taipa 999078, Macau, Peoples R China
[4] Univ Sci & Culture, Dept Mech Engn, Tehran, Iran
基金
中国博士后科学基金;
关键词
Home health care; Routing and scheduling; Multi -objective optimization; Cooperation evolutionary algorithm; Stochastic simulation; MATHEURISTIC APPROACH; MEMETIC ALGORITHM; OPTIMIZATION; SERVICE; PREFERENCE; DEMAND; SEARCH; MOEA/D; TRAVEL; MODEL;
D O I
10.1016/j.swevo.2022.101175
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Currently, population aging has aroused much concern in many countries since the elderly occupy a lot of social public resources in hospitals and nursing homes. Home health care (HHC) is treated as an alternative solution to serve the elderly community. In recent years, managing and organizing the operation of HHCs receive a great deal of attention. The HHC routing and scheduling problems attract huge amounts of interest from modeling and optimization areas. Nevertheless, there are rarely studies focusing on the cooperation of multiple HHC centers in such problems. This work addresses a multi-center, multi-objective and stochastic HHC routing and scheduling problem for minimizing the total operation cost and penalty cost incurred by earliness and delay service, where the caregivers' working time, customers' requirements and resource constraints are considered. Firstly, a multi -objective chance-constrained programming model is developed to formulate the studied problem. Secondly, a multi-objective cooperation evolutionary algorithm by using stochastic simulation is specially developed, in which two populations respectively perform global and local searches, and the cooperation of two populations is designed. The stochastic simulation approach is employed to evaluate the quality and feasibility of the obtained solutions. Finally, extensive experiments are performed on a set of test instances and three multi-objective optimization algorithms are compared to verify the performance of the proposed algorithm. The comparisons and discussions validate the competitiveness of the designed approach.
引用
收藏
页数:20
相关论文
共 50 条
  • [41] Multi-objective scheduling in hybrid flow shop: Evolutionary algorithms using multi-decoding framework
    Yu, Chunlong
    Andreotti, Pietro
    Semeraro, Quirico
    COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 147
  • [42] Using a metaheuristic algorithm for solving a home health care routing and scheduling problem
    Manavizadeh, Neda
    Farrokhi-Asl, Hamed
    Beiraghdar, Parya
    JOURNAL OF PROJECT MANAGEMENT, 2020, 5 (01) : 27 - 40
  • [43] On the Cooperation of Multiple Indicator-based Multi-Objective Evolutionary Algorithms
    Guillermo Falcon-Cardona, Jesus
    Emmerich, Michael T. M.
    Coello Coello, Carlos A.
    2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2019, : 2050 - 2057
  • [44] Multi-factorial evolutionary algorithm based novel solution approach for multi-objective pollution-routing problem
    Rauniyar, Amit
    Nath, Rahul
    Muhuri, Pranab K.
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 130 : 757 - 771
  • [45] AN EVOLUTIONARY ALGORITHM APPROACH TO MULTI-OBJECTIVE SCHEDULING OF SPACE NETWORK COMMUNICATIONS
    Johnston, Mark D.
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2008, 14 (03) : 367 - 376
  • [46] A multi-objective evolutionary algorithm guided by directed search for dynamic scheduling
    Wang, Du-Juan
    Liu, Feng
    Jin, Yaochu
    COMPUTERS & OPERATIONS RESEARCH, 2017, 79 : 279 - 290
  • [47] Dynamic Multi-Objective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem
    Lu, Hui
    Xu, Xin
    Zhang, Mengmeng
    Yin, Lijuan
    2015 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP), 2015, : 11 - 18
  • [48] An automatic multi-objective evolutionary algorithm for the hybrid flowshop scheduling problem with consistent sublots
    Zhang, Biao
    Pan, Quan-ke
    Meng, Lei-lei
    Lu, Chao
    Mou, Jian-hui
    Li, Jun-qing
    KNOWLEDGE-BASED SYSTEMS, 2022, 238
  • [49] Impact of the workload definition on the multi-objective home health care problem
    Decerle, J.
    Grunder, O.
    El Hassani, A. Hajjam
    Barakat, O.
    IFAC PAPERSONLINE, 2018, 51 (11): : 346 - 351
  • [50] Knowledge-driven adaptive evolutionary multi-objective scheduling algorithm for cloud workflows
    Zhang, Hui
    Zheng, Xiaojuan
    APPLIED SOFT COMPUTING, 2023, 146