A simulated annealing approach to explore temporal consolidation of healthcare courier services to reduce carbon emissions

The purpose of this paper is to investigate the effects of temporal consolidation (the intentional delay) of hospital laboratory samples / equipment for couriering to people and healthcare institutions worldwide, using a hill climbing genetic algorithm with integrated travelling salesman optimization function to determine the optimal configuration of vehicles in which to consolidate items, and the optimal route for each vehicle. Current hospital and courier service providers' practices centre on collecting items as and when they arrive for outward journeys at the hospital. Using data from a major London hospital this study evaluates 5 different consolidation scenarios, varying the length of time an item is delayed (ranging between 30 minutes to 10 hours). Findings indicate that consolidated approaches yielded reductions in vehicle numbers, between 116 and 258, compared to the current model of operation, but that the current model of operation is actually more environmentally efficient, generating 0.45 to 0.83 fewer metric tonnes of CO2, than consolidated approaches.