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三类调度问题的复合派遣算法及其在医疗运营管理中的应用

摘要第3-5页
Abstract第5-8页
1 Introduction第15-27页
    1.1 Background第15-21页
    1.2 Literature Review第21-27页
2 Parallel Machine Scheduling with Eligibility Constraints: A Composite Dispatching Rule to Minimize Total Weighted Tardiness第27-73页
    2.1 Introduction第27-32页
    2.2 Dominance Rules and Elimination Criteria第32-35页
    2.3 Factors and Statistics that Characterize a Problem Instance第35-38页
    2.4 Framework of the Heuristic第38-42页
    2.5 Estimation of Characteristic Factors (Phase I)第42-44页
    2.6 Determining Scaling Parameters (Phase II)第44-52页
        2.6.1 The Sequential Uniform Design Method and the Algorithm第46-48页
        2.6.2 Determining the Scaling Parameters第48-52页
    2.7 Performance Evaluation of ATCF Rule第52-64页
        2.7.1 Performance Comparisons Between ATC and ATCF Rules第53-56页
        2.7.2 Performance Comparisons Between Different Rules and the Near Optimal schedules第56-59页
        2.7.3 Testing on Real Data Set第59-64页
    2.8 Insights and Conclusions第64-73页
3 A Composite Dispatching Rule for Operating Room Scheduling with Machine Eligibility and Resource Constraints第73-94页
    3.1 Introduction第73-77页
    3.2 General Framework of the Heuristic第77-81页
        3.2.1 Factors Characterizing a Problem Instance第77-79页
        3.2.2 A General Framework第79-81页
    3.3 Sequential Uniform Design第81-83页
    3.4 A Case Study with Real Data第83-86页
        3.4.1 Data Description第83-84页
        3.4.2 Determining Scaling Parameters第84-86页
    3.5 Performance Evaluation of the Dispatching Rule第86-92页
        3.5.1 Further Comparison Between the AMFR Rule and Simulated Annealing Algorithm第90-92页
    3.6 Conclusions第92-94页
4 New Heuristic for A Two-Stage No-Wait Hybrid Flowshop with Eligibility Constraints第94-118页
    4.1 Introduction第94-102页
    4.2 Problem Formulation第102-104页
    4.3 Example Problem第104-106页
    4.4 MIP Model Formulation第106-108页
    4.5 Composite Dispatching Rule第108-113页
        4.5.1 The Sequential Uniform Design Method and the Algorithm第111-113页
    4.6 Computational Evaluation第113-116页
    4.7 Conclusions第116-118页
5 Conclusions第118-126页
    5.1 Summary第118-124页
    5.2 Future Work第124-126页
Bibliography第126-137页
Acknowledgements第137-139页
Research Achievements第139-141页

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