Demand Forecasting,Lot-sizing and Scheduling in the Multista

发布时间：2023-06-08 22:36

　　客户需求导向,使得制造系统需要在不同产品之间切换以满足顾客的定制需求;产品复杂性的增加,使得制造系统在不同产品之间的切换变得更加困难。因此,制造系统中的批量生产及调度(Lot-sizing and Scheduling,LSS)问题变得关键且具有挑战性。批量生产及调度决策的目标是确定最优生产批次和数量、机器分派(在多台机器的情况下)和生产排程,使得可以以最小的生产和库存成本满足顾客需求。批量生产及调度对制造系统的生产效率有深远的影响,但是在大多数解决方案方法中,批量生产及调度决策是分层进行的,即:在中期确定生产的批量,在短期考虑生产调度。尽管分层决策有助于降低问题的复杂性,但是,由于中期决策和短期决策之间存在相互依赖和相互影响,分层决策通常导致次优解决方案。因此,同时考虑这些决策以获得最佳的全局解决方案是必须的(Stadtler,2005)。在制造企业中,生产计划和调度通常从需求预测开始。准确的需求预测对于库存管理和生产计划至关重要。通常,制造经理的预测需要从部件级别到产品族级别的需求信息,形成一个层次性的时间序列。此外,随着新信息的出现,需求也会不断变化,因此需要使用更新的信息修正需...

【文章页数】：152 页

【学位级别】：博士

【文章目录】：
摘要
ABSTRACT
Chapter 1 Introduction
    1.1 Background
    1.2 Motivation and Objectives of the Thesis
    1.3 Problem Characteristics
    1.4 Structure of the Thesis
Chapter 2 Integrated Production Planning and Scheduling
    2.1 Supply Chain Planning and Advanced Planning Systems
    2.2 Demand Forecasting
    2.3 Production Planning and Scheduling
        2.3.1 Production Planning
        2.3.2 Integrated Production Planning and Scheduling
Chapter 3 Literature Review
    3.1 Forecasting under Correlated Demand
        3.1.1 Hierarchical Forecasting
        3.1.2 Demand Forecasting with Information Updating
    3.2 Lot-sizing and Scheduling
Chapter 4 Forecasting under Correlated Demand
    4.1 Hierarchical Forecasting
        4.1.1 Hierarchical Forecasting Approaches
        4.1.2 Performance Evaluation of the Forecasting Approaches
    4.2 Evolving Uncertain Demand Forecasts through Time
        4.2.1 Martingale Model of Forecast Evolution (MMFE)
        4.2.2 AR(1) Process with MMFE Framework
    4.3 Summary
Chapter 5 Integrated Lot Sizing and Scheduling: Models
    5.1 Multi-level Multi-Stage Simultaneous Lot–Sizing and SchedulingProblem
    5.2 The MMSLSP Model
    5.3 The MMSLSP-SCC Model
    5.4 Summary
Chapter 6 Integrated Lot Sizing and Scheduling: Solution Approaches
    6.1 Rolling Horizon Heuristics (RHH): Ideas and Description
    6.2 Computational Experiments
        6.2.1 Description of the Test Instances
        6.2.2 MMSLSP Model: The Results
        6.2.3 MMSLSP-SCC Model:The Results
    6.3 Summary
Chapter 7 Conclusions and Future Research
Bibliography
Acknowledgements
Research Papers
Projects
Resume



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