Final summary

Supply Chain Analytics in Python

Aaren Stubberfield

Supply Chain Analytics Mgr.

Summary

Reviewed what is Linear Programing (LP)
Reviewed PuLP and how it can be used with LP
Solving large scale models
- LpSum()
- LpVariable.dicts()
Logical constraints
Common constraint mistakes
Solving PuLP model
- printing decision variables, and objective

Summary

Sanity checking solution
Sensitivity Analysis
- Shadow Prices
- Slack
Simulation Testing
Capacitated Plant Location model - Case Study

Congratulations!

people shaking hands

Additional resources

For more on PuLP check out these additional resources:

https://www.coin-or.org/PuLP/
https://www.coin-or.org/
PuLP GitHub: https://github.com/coin-or/pulp
Google group: https://groups.google.com/forum/#!forum/pulp-or-discuss

Additional resources

For books related to the subject, check out these:

Bradley, Stephen P., et al. Applied Mathematical Programming. Addison-Wesley, 1977.
Chopra, Sunil, and Meindl, Peter. Supply Chain Management: Strategy, Planning, and Operations. Pearson Prentice-Hall, 2007.

Thank you!

Supply Chain Analytics in Python

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