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Genetic Algorithm for Orderplanning

Requirements

  • Python 3.7.3
  • PyGAD 2.18.1

Input CSV data examples (Do NOT include headers in file)

  • Copy and edit the example CSV files from example input data\ to imports\

Part & operations (The parts that can be produced)

  • Filename input_parts.csv
  • First column Part name
  • Add as many Operations as needed in following columns
Part name Operation Operation Operation Operation
Part1 Op1 Op2 Op3
Part2 Op1 Op2
Part3 Op1
Part4 Op1 Op2 Op3 Op4
Part5 Op1 Op2 Op3

Machines/Assets (The assets that can produce Parts)

  • Filename input_machines.csv
  • Part name & Operation name must match a Part in the Parts input
  • Time is the time required for the operation in the machine in minutes
Name Part name Operation name Time
Machine1 Part1 Op1 30
Machine1 Part1 Op2 25
Machine1 Part1 Op3 30
Machine1 Part2 Op1 25
Machine1 Part2 Op2 60
Machine1 Part2 Op3 55
Machine2 Part1 Op1 25
Machine2 Part1 Op2 60
Machine2 Part2 Op2 100

Work order list (The list of Parts that will be produced)

  • Filename input_workorders.csv
  • First column is the Part name to be produced
  • Amount of parts to be produced
Part name Amount
Part1 200
Part2 100
Part2 100
Part3 50
Part1 60
Part4 120
Part4 30
Part1 50
Part5 100

Output schedule

  • A schedule result file is output in the format exports\schedule_export_{run_id}_{total_time_in_minutes}.csv
Machine name Order id Order size Part name Operation Dependencies Scheduled Starttime Endtime
Machine2 4 60 Part1 Op1 True 0 1500
Machine2 0 200 Part1 Op1 True 1500 6500
Machine2 7 50 Part1 Op1 True 6500 7750
Machine2 setup setup setup setup True 7750 7810
Machine2 7 50 Part1 Op2 ['Op1'] True 7810 10810
Machine2 setup setup setup setup True 10810 10870
Machine2 2 100 Part2 Op2 ['Op1'] True 10870 20870
Machine1 2 100 Part2 Op1 True 0 2500
Machine1 1 100 Part2 Op1 True 2500 5000
Machine1 setup setup setup setup True 5000 5060
Machine1 0 200 Part1 Op2 ['Op1'] True 6500 11500
Machine1 setup setup setup setup True 11500 11560
Machine1 4 60 Part1 Op3 ['Op1', 'Op2'] True 11560 13360
Machine1 7 50 Part1 Op3 ['Op1', 'Op2'] True 13360 14860
Machine1 0 200 Part1 Op3 ['Op1', 'Op2'] True 14860 20860

GA configuration

The file ga_config.json can be used to edit parameters of the Genetic Algorithm

{
    "ga_parameters" : {

        "population_size" : 50,
        "generations" : 10000,
        "parents_mating" : 10,
        "keep_parents" : 5,
        "mutation_percent_of_genes" : 20,
        "saturation" : 500
    
        }
}

Run the application

To start the application, run the command: python ga.py --{optional arguments}

Arguments

  • --no_plot (Do not show the plot, default false)
  • --runs {x} (Number of runs(x), creates a separate schedule for every run, default 1)
  • --no_csv_export (Do not export a CSV file, default false)

Example: python ga.py --no_plot --runs 3 will create 3 output schedules in the exports folder, without displaying the plot during the runs.