A Mathematical Model for a Blood Supply Chain Network with the Robust Fuzzy Possibilistic Programming Approach: A Case Study at Namazi Hospital (original) (raw)
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Management of the blood as a vital and scarce resource is very important. The aim of this research is to present a novel mathematical model for designing a reliable blood supply chain network. This network consists of three main echelons including donors, collection facilities and demand points. At the collection echelon, three types of facilities are considered for receiving the bloods from the donors: main blood centers (MBCs), demountable collection centers (DCCs), and mobile blood facilities (MBFs). DCCs, and MBFs are mobile facilities that don’t have a permanent location and always move from a location to another one for collecting the bloods from the donors. The main difference between the MBFs and DCCs is that the DCCs can only visit at most a candidate location in every period, but the MBFs can visit more than one. Also, there are some other differences between their capacities and their costs. Both of DCCs and MBFs dispatch the collected bloods to the MBCs that are permanen...
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In the context of Blood Supply Chain Management, blood supply chain network design is one of the most pivotal planning problems. The stages of blood supply chain management comprise of blood collection, production, inventorying and distribution. The main challenges faced by supply channels are related to shortage, out datedness, and supply chain cost which needs to be minimized. In the current scenario, supply chain network design decisions should be flexible enough to operate under complex and uncertain business environments for many years. Decisionmaking under uncertainty is a crucial phenomenon and a large number of relevant publications have emphasized its importance. This paper makes an attempt towards reviewing the literature in the fields of blood supply chain network design under uncertainty. This study is organized into two phases. In the first phase, a discussion is made on the types of blood products, potential issues, and stages of blood supply chain management whereas i...
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European Journal of Engineering and Technology Research, 2019
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Due to the prominent role of blood in human life, designing an efficient blood supply chain in case of an emergency situation is essential especially considering blood compatibility. This research proposes a multi-objective model for emergency blood supply chain management considering blood compatibility, routing, and location-allocation decisions. The blood supply chain network consists of donors, collection facilities, laboratories, blood centers, and hospitals. The mathematical model aims to minimize total supply chain cost and time while maximizing minimum reliability of established routes by making decisions regarding location-allocation, blood flow, inventory levels, and optimal routes. In order to solve the problem, a novel algorithm called Multi-Objective Grey Wolf Optimizer is used and compared to two classical algorithms Multi-Objective Particle Swarm Optimization and Non-dominated Sorting Genetic Algorithm-II. Performance of the algorithms is evaluated in various test problems using powerful measures. Also, the application of the proposed model is investigated in a case study in Iran's capital, Tehran. Based on the results, important managerial insights are derived and optimal locations for facilities, inventory levels, routes and blood flow between facilities are determined.