Distribution Logistics Best Practice

Logistics and Supply Chain

Course Info

Duration: 1 Week

Type: In Classroom

Available Dates

Venue

  • Aug-08-2021

    Dubai

  • Aug-09-2021

    Istanbul

  • Aug-16-2021

    Paris

  • Aug-23-2021

    Madrid

  • Sep-06-2021

    Kuala Lumpur

  • Sep-06-2021

    London

  • Sep-12-2021

    Dubai

  • Sep-13-2021

    Istanbul

  • Sep-20-2021

    Paris

  • Sep-27-2021

    Madrid

  • Oct-04-2021

    Kuala Lumpur

  • Oct-04-2021

    London

  • Oct-10-2021

    Dubai

  • Oct-11-2021

    Istanbul

  • Oct-18-2021

    Paris

  • Oct-25-2021

    Madrid

  • Nov-08-2021

    Kuala Lumpur

  • Nov-08-2021

    London

  • Nov-14-2021

    Dubai

  • Nov-15-2021

    Istanbul

  • Nov-22-2021

    Paris

  • Nov-29-2021

    Madrid

  • Dec-06-2021

    Kuala Lumpur

  • Dec-06-2021

    London

  • Dec-12-2021

    Dubai

  • Dec-13-2021

    Istanbul

  • Dec-20-2021

    Paris

  • Dec-27-2021

    Madrid

  • Jan-03-2022

    Kuala Lumpur

  • Jan-03-2022

    London

  • Jan-09-2022

    Dubai

  • Jan-10-2022

    Istanbul

  • Jan-17-2022

    Paris

  • Jan-24-2022

    Madrid

  • Feb-07-2022

    Kuala Lumpur

  • Feb-07-2022

    London

  • Feb-13-2022

    Dubai

  • Feb-14-2022

    Istanbul

  • Feb-21-2022

    Paris

  • Feb-28-2022

    Madrid

  • Mar-07-2022

    Kuala Lumpur

  • Mar-07-2022

    London

  • Mar-13-2022

    Dubai

  • Mar-14-2022

    Istanbul

  • Mar-21-2022

    Paris

  • Mar-28-2022

    Madrid

  • Apr-04-2022

    Kuala Lumpur

  • Apr-04-2022

    London

  • Apr-10-2022

    Dubai

  • Apr-11-2022

    Istanbul

  • Apr-18-2022

    Paris

  • Apr-25-2022

    Madrid

Course Details

Course Outline

5 days course

 

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 of forecasting.
  • The variable to be predicted.
  • The forecasting processes.
  • 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 algorithm.
  • Setting the parameters.
  • Drawbacks and limitations.
  • Simple exponential smoothing.
  • 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-neighbour 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.

Course Video