Composite Facility Location Problems: A Case Study of Personalised Medicine

Abstract

Facility location problems (FLPs) are one of the most studied problem classes in supply chain management. However, despite the high number of research outputs, complex FLPs with large decision spaces and multi-objective formulations remain hard to solve. In this paper we introduce a multi-objective mathematical model for the FLP in personalised medicine, and apply a multi-stage algorithmic approach to solve it. In this case, the supply chain is circular and follows an on-demand and batch specific approach where the patient is also the donor. We solve the problem in a multi-stage manner, each stage optimising a sub-space of the larger decision space. In each stage we free up more decision variables to optimise, until eventually all decision variables defining the complete problem are made available for optimisation. A variant of the NSGA-II algorithm is used as solution method to solve both the complete problem and the different problem stages. Our results suggest that the multi-stage approach is able to find better solutions when compared to an approach that is given an equivalent number of evaluations but optimises the complete problem at once.