Introduction:
This comprehensive course presents a complete and balanced treatment of distribution logistics by covering both applications and the required theoretical background, therefore extending its reach to practitioners and students in a range of disciplines such as management, engineering, mathematics, and statistics. It serves as a useful reference for practitioners in the fields of applied mathematics and statistics, manufacturing engineering, business management, and operations research.
On completion of this course you should be able to:
- Deal with the quantitative approaches needed to handle real-life management problems.
- Identify the limitations and scope of applicability of the proposed quantitative tools.
- Discuss many issues on probability and statistics as well as mathematical programming
- Gain a broad understanding on Network design and transportation, and Demand forecasting
- Examines inventory control in single- and multi-echelon systems, and Incentives in the supply chain
- Identify Network routing problems and develop solution methods for symmetric TSP.
Course Outline
Supply chain management
- What do we mean by logistics?
- Plan of the chapter.
- Structure of production/distribution networks.
- Competition factors, cost drivers, and strategy.
- Competition factors.
- Cost drivers.
- Strategy.
- The role of inventories.
- A classical model: Economic Order Quantity.
- Cycle vs. capacity-induced stock.
- Dealing with uncertainty.
- Setting safety stocks.
- A two-stage decision process: Production planning in an assemble-to-order environment.
- Inventory deployment.
- Physical flows and transportation.
- Time horizons and hierarchical levels.
- Decision approaches.
- Information flows and decision rights.
- Quantitative models and methods.
- For further reading.
Network Design and Transportation
- The role of intermediate nodes in a distribution network.
- The risk pooling effect: reducing the uncertainty level.
- The role of transit points in transportation optimization.
- Location and flow optimization models.
- The transportation problem
- The minimum cost flow problem.
- The plant location problem
- Putting it all together
- Models involving nonlinear costs.
- For Further Reading.
Forecasting
- Overview on forecasting.
- The variable to be predicted.
- The forecasting process.
- Metrics for forecast errors.
- The Mean Error.
- Mean Absolute Deviation.
- Root Mean Square Error.
- Mean Percentage Error and Mean Absolute Percentage Error.
- ME%, MAD%, RMSE%.
- U Theil’s statistic.
- Using metrics of forecasting accuracy.
- A classification of forecasting methods
- Moving Average
- The demand model.
- The algorithm.
- Setting the parameters.
- Drawbacks and limitations.
- Simple exponential smoothing.
- The demand model.
- The algorithm.
- Setting the parameter.
- Initialization.
- Drawbacks and limitations.
- Exponential Smoothing with Trend.
- The demand model.
- The algorithm.
- Setting the parameters.
- Initialization.
- Drawbacks and limitations.
- Exponential smoothing with seasonality.
- The demand model.
- The algorithm.
- Setting the parameters.
- Initialization.
- Drawbacks and limitations.
- Smoothing with seasonality and trend.
- The demand model.
- The algorithm.
- Initialization.
- Simple linear regression.
- Setting up data for regression.
- Forecasting new products.
- The Delphi method and the committee process.
- Lancaster model: forecasting new products through products features.
- The early sales model.
- The Bass model.
- Limitations and drawbacks.
Inventory management with Deterministic Demand
- Economic Order Quantity.
- Robustness of EOQ model.
- Case of LT > 0: the (Q,R) model.
- Case of finite replenishment rate.
- Multi-item EOQ.
- The case of shared ordering costs.
- The multi-item case with a constraint on ordering capacity.
- Case of nonlinear costs.
- The case of variable demand with known variability.
Inventory control: the stochastic case.
- The newsvendor problem.
- Extensions of the Newsvendor problem.
- Multi-period problems.
- Fixed quantity: the (Q,R) model.
- Optimization of the (Q,R) model in case the stock out cost depends on the size of the stock out.
- (Q,R) system: case of constraint on the type II service level.
- Optimization of the (Q,R) model in case the cost of a stock-out depends on the occurrence of a stock out.(Q,R) system: case of constraint on type I service level.
- Periodic review: S and (s, S) policies.
- The S policy.
- The (s, S) policy.
Managing inventories in multiechelon supply chains
- Managing multi-echelon chains: Installation vs. Echelon Stock.
- Features of Installation and Echelon Stock logics.
- Coordination in the supply chain: the Bullwhip effect.
- A linear distribution chain with two echelons and certain demand.
- Arbores cent chain with two echelons: transit point with uncertain demand.
- A two echelon supply chain in case of stochastic demand.
Incentives in the supply chain
- Decisions on price: double marginalization.
- The first best solution: the vertically integrated firm.
- The vertically disintegrated case: independent manufacturer and retailer.
- A way out: designing incentive schemes.
- Decision on price in a competitive environment.
- The vertically disintegrated supply chain: independent manufacturer and retailer.
- Decision on inventories: the Newsvendor problem.
- The first best solution: the vertically integrated firm.
- The vertically disintegrated case: independent manufacturer and retailer.
- A way out: designing incentives and re-allocating decision rights.
- Decision on effort to produce and sell the product.
- The first best solution: the vertically integrated firm.
- The vertically disintegrated case: independent retailer and manufacturers.
- The case of efforts both at the upstream and downstream stage.
Vehicle Routing
- Network routing problems.
- Solution methods for symmetric TSP.
- Nearest-neighbor heuristic.
- Insertion-based heuristics.
- Local search methods.
- Solution methods for basic VRP.
- Constructive methods for VRP.
- Decomposition methods for VRP: cluster first, route second.
- Additional features of real-life VRP.
- Constructive methods for the VRP with time windows.
Related Training Courses
London , 1 Aug 2021 - One Week
The Market-Driven Supply Chain
London , 4 Jul 2021 - Two Weeks
