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Transportation Model (Powerco)

Transportation Model (Powerco). Transportation between supply and demand points, with the objective of minimizing cost. Send electric power from power plants to cities where power is needed at minimum cost. Objective: Minimize total cost of all shipments

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Transportation Model (Powerco)

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  1. Transportation Model (Powerco) • Transportation between supply and demand points, with the objective of minimizing cost. • Send electric power from power plants to cities where power is needed at minimum cost • Objective: Minimize total cost of all shipments • There is a unit shipping cost on each shipping route • This is multiplied by the amount shipped and summed over all routes

  2. 1 45 1 35 20 2 2 50 3 30 40 3 4 30 Powerco Contd. Constraints • Can’t ship more than is available from each power plant (supply point) • Must ship at least the amount needed to each city (demand point) Inputs • Unit shipping costs along each route • Amount of supply at each power plant • Demand at each city Decision Variables • The amount to ship along each route • There is a route from each supply point to each demand point • No other routes are allowed

  3. 40 40 40 40 0 0 0 0 4 1 2 3 25 75 40 60 Producing Sailboats at Sailco(Inventory Problem Modeled as Transportation Problem) • Produce sailboats over a multiperiod horizon to meet known (forecasted) demands on time • Regular-time and overtime labor are available • Minimize total production and holding costs Supply RT OT 10 10 0 0 0 Inventory Month Demand

  4. Objective • Minimize total costs, which include • Regular-time labor costs, Overtime labor costs, Inventory holding costs Inputs • Beginning inventory of sailboats • Maximum boats that can be produced per month with regular-time labor • Regular-time and overtime cost per boat • Unit holding cost per month in inventory • Monthly demands for boats Decision Variables • Number of boats to be supplied for each month from possible “supplies” • Supplies indicate the source of the boats: • Initial inventory • Regular-time labor in a particular month • Overtime labor in a particular month

  5. Job Assignments at MachincoThe Assignment Problem • Assign jobs to machines so that each job is assigned and each machine does at most one job • Minimize total time to do all jobs

  6. Job Assignments at MachincoModeling Approach • Model as a transportation problem, where all supplies and demands are 1 • Supplies correspond to machines (each with a supply of 1) • Demands correspond to jobs (each with a demand of 1)

  7. Job Assignments at MachincoObjective • Minimize the total time to complete all jobs

  8. Job Assignments at MachincoConstraints • Each job must be assigned to some machine • Each machine can do at most one job

  9. Job Assignments at MachincoInputs • The time required to do each job on each machine

  10. Job Assignments at MachincoDecision Variables • Which job-to-machine assignments to make

  11. Critical Path ModelBasic Problem • Analyze the length of time required to complete a project composed of activities with precedence relations (some activities can’t begin until others are completed) • See which activities are critical (the total project would be delayed if they were delayed)

  12. Critical Path ModelObjective • Schedule the activities in order to minimize the total project time

  13. Critical Path ModelConstraints • Because of built-in precedence relations, activities can’t begin until their predecessors are completed

  14. Critical Path ModelInputs • Precedence relations • Durations of activities

  15. Critical Path ModelDecision Variables • The times corresponding to the nodes in the project network • These are actually the earliest times certain activities can begin (e.g., node 2 is the earliest activities C and D can begin)

  16. Project Network(See “Chart1” sheet in Excel) • Precedence relations can be summarized in a graph called an “activity-on-arc” network • Each node corresponds to a point in time • Each arc corresponds to an activity • Precedence relations are obtained by joining certain nodes with certain arcs • Node 1 is a “start” node (time 0) • The last node is a “finish” node

  17. Shipping Food at FoodcoBasic Problem • Ship food from production plants to customers at least cost • Food can be shipped directly to customers or from plants to warehouses and then to customers • See “Chart1” sheet in Excel

  18. Shipping Food at FoodcoObjective • Minimize the total shipping cost • Each shipping cost is proportional to the amount shipped along the route

  19. Shipping Food at FoodcoConstraints • Arc capacities can’t be exceeded • There must be “flow balance” at each node • There is positive net outflow at each supply point (plants) • There is zero net outflow at each transshipment point (warehouses) • There is positive net inflow (negative net outflow) at each demand point (customers)

  20. Shipping Food at FoodcoInputs • Unit shipping costs • Arc capacities • Supplies at supply points • Demands at demand points

  21. Shipping Food at FoodcoDecision Variables • Flows along all arcs • Includes flows into dummy node (which is excess capacity not shipped)

  22. Maximum Oil Flow at SuncoBasic Problem • Ship as much oil (per unit time) from a “source” node to a “sink” (destination) node as possible along a given network of pipelines • See “Chart1” sheet in Excel

  23. Maximum Oil Flow at SuncoObjective • Maximize the total flow from source to sink per unit of time

  24. Maximum Oil Flow at SuncoConstraints • Don’t exceed arc (pipeline) capacities • Achieve flow balance at each node • By adding a dummy arc from the sink to the source, we can let all net outflows be zero

  25. Maximum Oil Flow at SuncoInputs • Arc capacities • These indicate how much oil can go through a given pipeline per unit of time

  26. Maximum Oil Flow at SuncoDecision Variables • Arc flows • These include the flow along the dummy arc (which isn’t an actual physical flow)

  27. Shortest Route: Car Replacement Basic Problem • Decide on a least-cost purchasing/selling strategy for cars, given that a car is needed at all times • Economic reason for selling cars is that maintenance costs increase with age and trade-in value decreases with age

  28. Shortest Route: Car ReplacementSolution Strategy • Model as a shortest route problem • Origin is year 1 • Destination is end of planning horizon • Any path from node 1 to node 6 represents a replacement strategy

  29. Shortest Route: Car Replacement Objective • Minimize the total cost of owning a car during the planning horizon, including: • The cost of purchasing new cars • The maintenance cost of owning cars • The trade-in value of replaced cars

  30. Shortest Route: Car Replacement Constraints • Flow balance constraints

  31. Shortest Route: Car Replacement Inputs • Length of planning horizon • Cost of a new car • Maintenance cost per year, which increases with the age of the car • Trade-in value of car, which decreases with the age of the car

  32. Shortest Route: Purchasing CarsDecision Variables • Flows on the arcs

  33. Investing at StockcoBasic Problem • Choose the investments that stay within a budget and maximize the NPV • Each investment is an all-or-nothing decision

  34. Investing at Stockco Objective • Maximize the NPV of the investments chosen

  35. Investing at Stockco Constraints • Cash spent on investments can’t be greater than cash available

  36. Investing at Stockco Inputs • Amount of cash required for each investment • Amount of NPV obtained from each investment

  37. Investing at Stockco Decision variables • Whether to invest or not in each investment • This is indicated by a 0-1 changing cell, which is 1 for an investment that is chosen, 0 otherwise

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