Solving optimization problems in a business setting can be a significant challenge. There is a constant tension between delivering quick prototypes to prove value and building robust tools.

At Fonterra, a New Zealand dairy co-operative, one of our planning problems concerns organic milk production. Due to low volumes or organic-certified milk, organic production planning takes place outside the usual planning process. The constraints around organic problems are complex, and there is considerable value to be derived from a quality plan. These factors make organic planning a perfect candidate for a stand-alone optimization project within the business.

During this project, JuMP has been an invaluable tool in several ways. Using JuMP, it has been trivial to develop quick prototypes and experimental features, without sacrificing the robustness of the end-product. JuMP enables our team to be creative during the process and try new things on the fly. We can quickly respond to feedback from end users, which helps build a close relationship and ensure the continued success of the project. JuMP is also a reliable tool for building larger optimization applications, enabling the Data Science team at Fonterra to easily incorporate different multi-objective optimization approaches, optional cuts and complex conditional constraints into the model.

Thanks to JuMP, we have been able to mitigate the problem outlined at the start of the abstract, and secure key user engagement through continuous proof of value while delivering robust software.