客戶需求導(dǎo)向,使得制造系統(tǒng)需要在不同產(chǎn)品之間切換以滿足顧客的定制需求;產(chǎn)品復(fù)雜性的增加,使得制造系統(tǒng)在不同產(chǎn)品之間的切換變得更加困難。因此,制造系統(tǒng)中的批量生產(chǎn)及調(diào)度(Lot-sizing and Scheduling,LSS)問(wèn)題變得關(guān)鍵且具有挑戰(zhàn)性。批量生產(chǎn)及調(diào)度決策的目標(biāo)是確定最優(yōu)生產(chǎn)批次和數(shù)量、機(jī)器分派(在多臺(tái)機(jī)器的情況下)和生產(chǎn)排程,使得可以以最小的生產(chǎn)和庫(kù)存成本滿足顧客需求。批量生產(chǎn)及調(diào)度對(duì)制造系統(tǒng)的生產(chǎn)效率有深遠(yuǎn)的影響,但是在大多數(shù)解決方案方法中,批量生產(chǎn)及調(diào)度決策是分層進(jìn)行的,即:在中期確定生產(chǎn)的批量,在短期考慮生產(chǎn)調(diào)度。盡管分層決策有助于降低問(wèn)題的復(fù)雜性,但是,由于中期決策和短期決策之間存在相互依賴和相互影響,分層決策通常導(dǎo)致次優(yōu)解決方案。因此,同時(shí)考慮這些決策以獲得最佳的全局解決方案是必須的(Stadtler,2005)。在制造企業(yè)中,生產(chǎn)計(jì)劃和調(diào)度通常從需求預(yù)測(cè)開(kāi)始。準(zhǔn)確的需求預(yù)測(cè)對(duì)于庫(kù)存管理和生產(chǎn)計(jì)劃至關(guān)重要。通常,制造經(jīng)理的預(yù)測(cè)需要從部件級(jí)別到產(chǎn)品族級(jí)別的需求信息,形成一個(gè)層次性的時(shí)間序列。此外,隨著新信息的出現(xiàn),需求也會(huì)不斷變化,因此需要使用更新的信息修正需...

【文章頁(yè)數(shù)】：152 頁(yè)

【學(xué)位級(jí)別】：博士

【文章目錄】：
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



本文編號(hào)：3832631