DocumentCode :
2823982
Title :
Optimizing the assignment of blood in a blood banking system: Some initial results
Author :
Adewumi, Aderemi ; Budlender, Nigel ; Olusanya, Micheal
Author_Institution :
Sch. of Comput. Sci., Univ. of KwaZulu-Natal, Durban, South Africa
fYear :
2012
fDate :
10-15 June 2012
Firstpage :
1
Lastpage :
6
Abstract :
Due to the critical blood shortages in South Africa and around the world, the assignment of blood can be considered an important real world optimization problem. This paper presents a mathematical model that facilitates good management and assignment of red blood cell units in order to minimize the quantity of imported units from outside the system. The model makes use of the Multiple Knapsack Algorithm, which is implemented using several optimization techniques, in order to determine the most optimal assignments. These include a Genetic Algorithm (GA), Adaptive Genetic Algorithm (AGA), Simulated Annealing Genetic Algorithm (SAGA), Adaptive Simulated Annealing Genetic Algorithm (ASAGA) and finally a Hill Climbing (HC) Algorithm. All techniques were capable of achieving the optimal fitnesses. The AGA, SAGA and ASAGA provide some desirable results over the standard GA, whilst the HC algorithm proves to demonstrate the best results overall.
Keywords :
blood; genetic algorithms; knapsack problems; simulated annealing; ASAGA; HC algorithm; South Africa; adaptive genetic algorithm; adaptive simulated annealing genetic algorithm; blood banking system; critical blood shortages; hill climbing algorithm; mathematical model; multiple knapsack algorithm; optimization problem; red blood cell units; Banking; Biological cells; Genetic algorithms; Heuristic algorithms; Optimization; Red blood cells; Blood Assignment problem; Genetic Algorithms; Hill Climbing; Optimization; Real-World Problem; Simulated Annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
Type :
conf
DOI :
10.1109/CEC.2012.6256633
Filename :
6256633
Link To Document :
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