Module content |
- Review of the general framework for the planning and control of manufacturing and service systems
- Deterministic Lot Sizing Models of Inventory Management
- Basic single item EOQ/EPQ, shortage, all unit and marginal discount models
- Discrete time and quantity models and their solution approaches
- Multi item models including shared resource with constraints, common cycle, basic cycle, power of two and Economic Lot Scheduling models
- Multi echelon and foundational supply chain inventory models
- Models with building blocks for contemporary research areas in deterministic inventory models: deterioration, delayed payment, recoverable stock, non-linear demand rate, non-linear production rate, growing items, demand-, time-, stock and price- dependent models and other emerging lot sizing model block areas
- Finite Job Scheduling Models and their Solution Techniques
- Scheduling notation, dispatch rules and their solution characteristics
- Flow shop models, job shop models, selected variants and their solution algorithms
- Formulation of basic mathematical programming models for scheduling problems
- Solution techniques for scheduling LP models and analysis of solution heuristics: review of general mathematical proof techniques; growth functions and asymptotic bounds of solution algorithms; NPcompleteness, orst- and average-case behaviour of algorithms and illustration with some basic problems; analysis of selected exact scheduling solution algorithms; discussion of selected heuristic and meta heuristic alternatives and their time complexity; design and analysis of hybrid-solutions for NP-hard scheduling problems; scheduling solution/result analysis
- Structural Models of Supply Chain Factors and their Relationships
- Review of descriptive statistics, statistical inference, estimation and hypothesis testing principles
- Multivariate statistical problems and foundational regression analysis
- Foundations of Structural Equation Modelling (SEM) and its representations
- Foundational Principal Component Analysis (PCA) and Factor Analysis (FA)
- Introduction to Covariance Based (CB) and Partial Least Square (PLS) SEM approaches
- Procedure for implementing PLS SEM and interpretation of solution output
- Cases of Supply Chain SEM models and their analysis with PLS SEM using Smart PLS
At the beginning of the contact sessions, students may be allowed, based on the class composition, to suggest one additional area they may want us to discuss. This may include assembly line balancing, aggregate planning, forecasting or some areas of modern manufacturing flow control like Lean/JIT, Synchronous manufacturing/TOC, CONWIP, POLCA, COBACABANA, or DDMRP. This is not examinable, but may help students with such needs, if they are sizable and the need is identified. |
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