Cutting Stock Problem

Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually of fixed size).

New to Cutting Stock Problem? Understand Visually

This implementation of CSP tries to answer

How to minimize number of stock items used while cutting customer order

while doing so, it also caters

How to cut the stock for customer orders so that waste is minimum

The OR Tools also helps us in calculating the number of possible solutions for your problem. So in addition, we can also compute

In how many ways can we cut given order from fixed size Stock?

Quick Usage

This is how CSP Tools looks in action. Click CSP Tool to use it

Libraries

• Google OR-Tools

Quick Start

Install Pipenv, if not already installed

$ pip3 install --user pipenv

Clone this project and install packages

$ git clone https://github.com/emadehsan/csp
$ cd csp
$ pipenv install

# activate env
$ pipenv shell

Run

If you run the stock_cutter_1d.py file directly, it runs the example which uses 120 as length of stock Rod and generates some customer rods to cut. You can update these at the end of stock_cutter_1d.py.

(csp) $ python csp/stock_cutter_1d.py

Output:

numRollsUsed 5
Status: OPTIMAL
Roll #0: [0.0, [33, 33, 18, 18, 18]]
Roll #1: [2.9999999999999925, [33, 30, 18, 18, 18]]
Roll #2: [5.999999999999993, [30, 30, 18, 18, 18]]
Roll #3: [2.9999999999999987, [33, 33, 33, 18]]
Roll #4: [21.0, [33, 33, 33]]```

Using input file

If you want to describe your inputs in a file, infile.txt describes the expected format

(csp) $ python3 csp/stock_cutter_1d.py infile.txt

Thinks to keep in mind

• Works with integers only: IP (Integer Programming) problems working with integers only. If you have some values that have decimal part, you can multiply all of your inputs with some number that will make them integers (or close estimation).
• You cannot specify units: Whether your input is in Inches or Meters, you have to keep a record of that yourself and conversions if any.

Resources

The whole code for this project is taken from Serge Kruk's

• Practical Python AI Projects: Mathematical Models of Optimization Problems with Google OR-Tools
• Repository of the code in Serge's book