Optimisation – the key to solving complex network challenges


BearingPoint has been using analytics to support its supply chain projects for many years. Optimisation is a key tool, especially for network optimisation projects, but typically would be combined with other analytical methods.

We will present a short overview of the methodology to assess the future store network for a retailer, taking into account the changing behaviours of customers, with a blend of in-person and digital shopping.

Using client examples, we will demonstrate the mixture of machine learning (mostly clustering and determination of loss functions) and optimisation (for the actual network optimisation), to combine the statistical elements of the question with the prescriptive outputs generated through the optimisation model.

Finally, we will highlight some key outputs from a recent study as well as some lessons learned.



Emile Naus, Partner, BearingPoint

Emile is the UK Partner for Operations. He has 30 years’ experience in designing, building and running supply chains. He was previously Head of Logistics Strategy for Marks and Spencer and Long Term Planning Manager for Tesco.


Paul Derbyshire, Senior Technical Advisor, BearingPoint

Paul is a Senior Technical Advisor within the Operations team at BearingPoint UK. Paul has over 20 years’ experience in supply chain analytics and modelling. Prior to BearingPoint, Paul worked as consultant, implementing planning and scheduling optimisation solutions in the Process industries.


Try Gurobi for Free

Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.

Evaluation License
Get a free, full-featured license of the Gurobi Optimizer to experience the performance, support, benchmarking and tuning services we provide as part of our product offering.
Academic License
Gurobi supports the teaching and use of optimization within academic institutions. We offer free, full-featured copies of Gurobi for use in class, and for research.
Cloud Trial

Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.