Dissertation > Excellent graduate degree dissertation topics show

Belief-Rule Inference Method and its Applications in Inventory and Production Operations Management

Author: LiBin
Tutor: WangHongWei; YangJianBo
School: Huazhong University of Science and Technology
Course: Systems Engineering
Keywords: Evidential reasoning theory Belief-rule-based inference theory Expert Systems Supply chain management Production and operationmanagement Inventory control Aggregate production planning Uncertainty
CLC: F224
Type: PhD thesis
Year: 2012
Downloads: 133
Quote: 0
Read: Download Dissertation


With the rapid development of information and manufacturing technologies andgradually shortened product life cycle, inventory and production operations management inenterprise and supply chain management are facing more and more uncertainties, in whichthe biggest source is demand uncertianty. It has become a hot spot nowadays whichattracted much attention from researchers and practitioners to systematically analyze andsolve inventory and production operations management problems under uncertainties. Theanalytical method and simulation method have limitations with respects to computationalcomplexity, portability, and the expression ability of domain knowledge and uncertaininformation. Heuristic methods can effectively use expert domain knowledge and aresuitable for complex, changing and resource constrained environment, especially theartificial intelligence based heuristic methods have favorable capability to express andtransact uncertainty. Facing dynamically changing inventory and production operationalenvironments with frequent replanning and interconnected resource constraints, researcherand practitioner more and more tend to use AI based heuristic methods.As an AI based heuristic method, belief-rule-based inference (BRBI) method isproposed based on evidential reasoning theory and production rule based expert system fordealing with uncertain problems. This thesis studies deeply the BRBI method, and applies itto inventory and production operations management problems under uncertainty. The mainresearch works are as follows:This thesis introduces the foundation of BRBI theory, outlines the application modesand application mechanisms of BRBI method, and proposes a BRBI approach with intervaluncertain inputs. The application modes of the BRBI model are classified into systemapproximator and system controller. The application methanisms provide the key elimentsof the BRBI model, which has instruction and support functions to improvement andapplication of the BRBI method.For inventory control problem under nonstationary uncertain demand, abelief-rule-based inventory control (BRB-IC) method is proposed considering bothbackorder case and lost sales case. An optimal base stock policy under normal forecast erroris proved as a quantitative expert knowledge to initialize the belief-rule-base. A numericalexample and an auto4S store case study are provided to examine the BRB-IC method bycomparison with existing adaptive method, heuristic method, myopic method,certainty-equivalent-control, and robust optimization.For structure and parameter identifications of the belief-rule-base, a simultaneous identification approach and an asynchronous identification approach are developed andcompared. In the asynchronous approach, a belief K-means clustering algorithm is putforward for structure identification. For aggregate production planning (APP) underuncertain demand, a hierarchical BRBI method for APP is proposed including bothcontinuous and switching modes. The simultaneous identification approach andasynchronous identification approach are applied to identify the structure and parameter ofBRB. An automotive case study and the Pittsburgh paint factory example are provided. TheBRBI method is compared with nonlinear interval number programming, linear decisionrule and production switching heuristic. The sensitivity of BRBI method is analyzed underdifferent cost structures.For belief-rule-inference model under interval inputs, structure identification andparameter identification models in the asynchronous approach, corresponding genetic-conjugate gradient algorithms are proposed and applied into centralized supply chainmanagement problem under uncertain demand. The producer and distributor’s hierarchicalBRBI framework is constructed and their inference models and order policies are provided.In an automotive case study, the superiority of the genetic-conjugate gradient algorithmsover existing algorithms are provided, and the BRBI method is compared with the robustoptimization method.

Related Dissertations

  1. K Company’s Improving Planning and Forecasting for the Reasonable Allocation of Inventory,F224
  2. Design and Application of Scope Anti-Shake System,TH743
  3. The Software Component Modeling Method Based on Feature and Its Application in VMI Management System,TP311.52
  4. The Research and Design of Middle-Small Enterprises Purchase-Sales-Inventory Management System,TP311.52
  5. Stability Analysis and Controller Design for Discrete-Time Switched System,TP13
  6. Stability Analysis of Systems with Time Delays,TP13
  7. Study on Green Supply Chain Management Based on Stakeholders Theory,F274
  8. Health-based and Ecological Risk Assessment of Contaminated Sites,X820.4
  9. The Evaluation and Forecasting Research on Uncertainty Systems Method of Student Achievement,G642.4
  10. Effects of the Therapeutic Communication System Intervention on the Illness Uncertainty of Preoperative Colorectal Cancer Patients,R473.73
  11. Research on the Supply Chain Management of Book Distribution Industry,F274
  12. Uncertainty and metafiction : \,I712.074
  13. Information Aversion,G201
  14. Context of triple play and supply chain procurement,G229.2-F
  15. CP Rim region and implementation of supply chain optimization,F426.22
  16. Genetic Algorithm in logistics and warehousing Optimization Research,F259.2
  17. Company X railway owned car management problems and countermeasures research,F426.22
  18. Deep Reasonable Economic Mining Depth Analysis Based on Uncertainty Disaster Factors,TD823
  19. Based on Fuzzy Neural Network Fault Diagnosis of Expert Systems,TP183
  20. Research about Material Inventory Control of Coal Enterprise Based on TOC,F253.4
  21. Social Anxiety Research in Transition Period,C912.6

CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
© 2012 www.DissertationTopic.Net  Mobile