Chapter 6 - Distribution & Network Models

Flashcard 1

Term: Network Model
Definition: A mathematical representation of a system where items flow between locations.
Example: A logistics network where products move from factories to warehouses to customers.

Flashcard 2

Term: Node
Definition: A point in a network representing a location (e.g., factory, warehouse, store).
Example: Amazon’s fulfillment centers.

Flashcard 3

Term: Arc
Definition: A connection between nodes representing a path, road, or route.
Example: A shipping lane between two ports.

Flashcard 4

Term: Transportation Problem
Definition: A model that minimizes shipping costs between multiple suppliers and demand points.
Example: A bakery shipping bread from two plants to five grocery stores.

Flashcard 5

Term: Balanced Transportation Problem
Definition: A transportation problem where total supply = total demand.
Example: A factory with 100 units of supply and customers requiring 100 units.

Flashcard 6

Term: Unbalanced Transportation Problem
Definition: A transportation problem where total supply ≠ total demand. Requires a dummy source/destination.
Example: A warehouse with 120 units shipping to stores that need only 100 units.

Flashcard 7

Term: Dummy Source/Destination
Definition: A fictitious node added to balance an unbalanced transportation problem.
Example: If demand is higher than supply, a dummy supplier is added with zero cost.

Flashcard 8

Term: Transshipment Problem
Definition: A transportation problem that allows shipments to pass through intermediate nodes.
Example: Goods moving from a factory → warehouse → customer instead of direct delivery.

Flashcard 9

Term: Flow Conservation
Definition: In a transshipment model, total inflow = outflow at an intermediate node.
Example: If a warehouse receives 100 items, it must ship 100 items.

Flashcard 10

Term: Assignment Problem
Definition: A special case of transportation where workers are assigned to tasks at minimum cost.
Example: Assigning 3 workers to 3 tasks based on their efficiency.

Flashcard 11

Term: Hungarian Algorithm
Definition: A specialized method to solve assignment problems optimally.
Example: Used to assign employees to shifts efficiently.

Flashcard 12

Term: Shortest-Route Problem
Definition: A model that finds the shortest path between two nodes in a network.
Example: Google Maps finding the fastest route to work.

Flashcard 13

Term: Dijkstra’s Algorithm
Definition: A method to find the shortest path in a network with non-negative weights.
Example: Used in GPS navigation to find the quickest route.

Flashcard 14

Term: Bellman-Ford Algorithm
Definition: A method to find the shortest path that works with negative weights.
Example: Used in financial modeling where costs may decrease over time.

Flashcard 15

Term: Maximal Flow Problem
Definition: A model that determines the maximum possible flow from a source node to a sink node.
Example: Finding the max capacity of an oil pipeline network.

Flashcard 16

Term: Source Node
Definition: The starting point of flow in a maximal flow problem.
Example: A water reservoir supplying a city.

Flashcard 17

Term: Sink Node
Definition: The final destination where flow is collected.
Example: A city receiving water from a reservoir.

Flashcard 18

Term: Flow Capacity
Definition: The maximum amount of flow allowed through an arc.
Example: A bridge that can handle 5,000 vehicles per hour.

Flashcard 19

Term: Ford-Fulkerson Algorithm
Definition: A method used to find the maximum flow in a network.
Example: Used in internet bandwidth allocation to maximize data transfer.