Simulation-optimization model for production planning in the blood supply chain.
Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.
Southampton Business School, University of Southampton, Southampton, SO17 1BJ, UK. Afo1e13@soton.ac.uk.|Universidad Icesi, Calle 18 No. 122 - 135, Cali, Colombia. Afo1e13@soton.ac.uk.
Andres F
AF
Osorio
Southampton Business School, University of Southampton, Southampton, SO17 1BJ, UK.
Sally C
SC
Brailsford
Mathematical Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
Honora K
HK
Smith
Hemocentro Distrital, Cra. 32 No 12 - 81, Bogotá, Colombia.
Sonia P
SP
Forero-Matiz
Hemocentro Distrital, Cra. 32 No 12 - 81, Bogotá, Colombia.
Bernardo A
BA
Camacho-Rodríguez
D001771:Blood Banks / Q000191:economics / Q000458:organization & administration*; D001782:Blood Donors; D001793:Blood Preservation; D003105:Colombia; D003198:Computer Simulation; D006801:Humans; D017146:Models, Organizational; D019982:Organizational Case Studies; D015397:Program Evaluation; D000094902:Blood Banking / Q000379:methods*
Blood collection; Blood supply chain; Optimization; Production planning; Simulation