Proof-of-concept to determine feasibility of migrating operations research engine from Maple to Python.

Several of PerformanSC’s data driven performance improvement inputs result from optimisation routines developed on their proprietary operations research toolsets using the Maple programming language. Whilst this technology has served its purpose up to this point, future business needs are likely to require capabilities that solve larger problems with larger data sets.

Phyton is a leading technology within the Data Science area, with most of the recent machine learning and AI work being conducted in and around Python. Working with the software design team in the Design+ Technology Gateway, the company wished to explore the possibility of moving to an open-source technology infrastructure (based around Python programming language), to address two specific supply chain optimisation problems – location-type and transport-type problems.