Linear Programming Optimisation

Type

pyspark2inputs

Class

fire.nodes.lpo.NodeLinearProgrammingOptimisation

Fields

Name	Title	Description
objective	Objective	Minimise or Maximise the objective function?

Details

Select Weather to Maximise or minimise the objective function :

The Node takes in two dataframes as Input:

Lower edge Dataframe must have these columns :

var, value, type, relationship and bound which would help declare the Decision Variables

Higher Edge Datafrane must have these column along with all the var Decision variables which were declared in the above dataframe :

constarint,x1,x2,x3,relationship,value

These would create the constraint equations from the dataframe.

After solving the equations the Output is :

Variables Names and Values,Constraints Names and Values & Objective Value

Examples

Incoming Dataframe has following rows:

var           |    value     |    type        |    relationship    |    bound
-------------------------------------------------------------------------------------
tables        |    40        |    Integer     |    >=             |    0
chairs        |    30        |    Integer     |    >=             |    0
bookcases     |    35        |    Continuous  |    <=             |    0

constraint | tables | chairs | bookcases | relationship | value
-----------------------------------------------------------------
labor      | 2      | 1      | 2.5       | <=           | 60
machine    | 0.8    | 0.6    | 1         | <=           | 16
wood       | 30     | 20     | 30        | <=           | 400
tables     | 1      | 0      | 0         | >=           | 10

The above table would correspond to equations:

2 * tables + 1 * chairs + 2.5 * bookcases <= 60, “labour”

0.8 * tables + 0.6 * chairs + 1 * bookcases <= 16, “machine”

30 * tables + 20 * chairs + 30 * bookcases <= 400, “wood”

2 * tables + 0 * chairs + 0 * bookcases >= 10, “tables”

The output for the above Problem when the Objective function is Maximised is:

Variables Names and Values

bookcases = 0.0

chairs = 5.0

tables = 10.0

Constraints Names and Values

Labor = -35.0

machine = -5.0

wood = 0.0

tables = 0.0

Objective Value is : 550.0