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A New Location-Allocation Model for Blood Distribution Considering Limited Lifespan Under Fuzzy Conditions: A Real Application

A New Location-Allocation Model for Blood Distribution Considering Limited Lifespan Under Fuzzy Conditions: A Real Application

Vahidreza Ghezavati, Yasser Moeini
Copyright: © 2018 |Volume: 9 |Issue: 4 |Pages: 23
ISSN: 1947-8569|EISSN: 1947-8577|EISBN13: 9781522544210|DOI: 10.4018/IJSDS.2018100107
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MLA

Ghezavati, Vahidreza, and Yasser Moeini. "A New Location-Allocation Model for Blood Distribution Considering Limited Lifespan Under Fuzzy Conditions: A Real Application." IJSDS vol.9, no.4 2018: pp.105-127. http://doi.org/10.4018/IJSDS.2018100107

APA

Ghezavati, V. & Moeini, Y. (2018). A New Location-Allocation Model for Blood Distribution Considering Limited Lifespan Under Fuzzy Conditions: A Real Application. International Journal of Strategic Decision Sciences (IJSDS), 9(4), 105-127. http://doi.org/10.4018/IJSDS.2018100107

Chicago

Ghezavati, Vahidreza, and Yasser Moeini. "A New Location-Allocation Model for Blood Distribution Considering Limited Lifespan Under Fuzzy Conditions: A Real Application," International Journal of Strategic Decision Sciences (IJSDS) 9, no.4: 105-127. http://doi.org/10.4018/IJSDS.2018100107

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Abstract

One of the important centers among the health facilities is the centers of blood donations. Blood donors may not be able to donate because of the long distance between blood donation centers and their location. In this article, a dynamic hierarchical location-allocation model with fuzzy conditions is offered to locate blood donation centers and assign blood donors to these centers. The limited life span for blood is considered as the most important model assumption. Because of this in real world situations, fuzzy theory and uncertainty approaches will be applied to formulate the problem. In addition, the total amount of donated blood for each area is not definite. The ratio between different expiration dates and blood depends on blood donations during different periods, so this parameter is faced with uncertainty. Numerical examples are presented to show benefits the and the performance of proposed model. In addition, the proposed model is run for a real-world case in the city of Tehran, Iran. The results indicate that applying the proposed optimization model can improve amount of shortage and inventory in the blood network against current status in the case study. Besides, experiments indicate that applying fuzzy theory for this problem can reduce 12.5% of total costs via the certain formulation.

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