Logistics optimization w/ PyMC3?

I’m curious if anyone come across a resource oriented around PyMC3 for logistics, supply chain, inventory, …, optimization?

Most resources I stumble on take a deterministic approach (linear programming.) You can supply point estimates for each constraint, however, it’s not at all obvious how to approximate a global optimal configuration of parameters given simulated/sampled constraints.

For example, if you’re optimizing the number of items on hand in a warehouse, you might take into account the price an average customer is willing to pay (demand) and the number of units sold in a given time interval. To make use of linear programming, you’d need to use MLE estimates (or the means of a sampler outputs.)

More of an open ended question on- who is actively using PyMC3 for some form of logistics/supply chain analytics and optimization?

@twiecki has a blog article on this that you might find interesting: Using Bayesian Decision Making to Optimize Supply Chains — While My MCMC Gently Samples

1 Like