Volume 54, Number 4, July-August 2020
|1013 - 1025
|13 May 2020
A new model and a Monte Carlo based Particle Swarm Optimization algorithm for the stochastic blood assignment problem
Department of Management, Faculty of Economics and Administrative Sciences Ferdowsi University of Mashhad, Mashhad, Iran
2 Department of Management, Economics and Accounting Faculty Yazd University, Yazd, Iran
3 Department of Industrial Engineering, Faculty of Engineering Ferdowsi University of Mashhad, Mashhad, Iran
* Corresponding author: firstname.lastname@example.org
Accepted: 10 February 2020
Blood and its products, in some cases, are the only vital and sanative medicine for the patients. Each donated blood unit is a valuable asset to protect the patients’ lives, and it should be avoided waste and non-optimal consumption. The assignment of blood and its products to hospitals is one of assignment problems, in which finding the optimal solution can lead to a reduction in mortality and waste of expenditure. In this research, a new model for the assignment of blood products in a stochastic environment is presented. The goal of the model is to minimize the preparation, deficiency and waste cost of blood products, while considering the constraints of the problem. The stochastic model is implemented in a real case and is solved by the Monte Carlo simulation method. Then, a random model is settled in a real problem in Yazd city and it is solved via a Monte Carlo based Particle Swarm Optimization algorithm. The results reveal that the solution of the hybrid algorithm can significantly reduce the costs of preparation, deficiency and waste of blood products.
Mathematics Subject Classification: 90B80 / 90c15 / 65c05 / 90c27
Key words: Assignment problem / stochastic programming / Monte Carlo simulation / Particle Swarm Optimization / hybrid algorithm / blood products
© EDP Sciences, ROADEF, SMAI 2020
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