Modeling and optimization of a reliable blood supply chain network in crisis considering blood compatibility using MOGWO

被引:34
作者
Ghorashi, Seyed Behzad [1 ]
Hamedi, Maryam [1 ]
Sadeghian, Ramin [1 ]
机构
[1] Payame Noor Univ, Dept Ind Engn, Fac Engn, Tehran, Iran
关键词
Blood supply chain; Disaster management; Reliability; Multi-objective optimization; Supply chain management; Meta-heuristic algorithms; VENDOR MANAGED INVENTORY; MULTIOBJECTIVE OPTIMIZATION; EVOLUTIONARY ALGORITHMS; QUANTITY MODEL; EOQ MODEL; DESIGN; EFFICIENT;
D O I
10.1007/s00521-019-04343-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:12173 / 12200
页数:28
相关论文
共 54 条
[31]   Grey Wolf Optimizer [J].
Mirjalili, Seyedali ;
Mirjalili, Seyed Mohammad ;
Lewis, Andrew .
ADVANCES IN ENGINEERING SOFTWARE, 2014, 69 :46-61
[32]   Grasshopper optimization algorithm for multi-objective optimization problems [J].
Mirjalili, Seyedeh Zahra ;
Mirjalili, Seyedali ;
Saremi, Shahrzad ;
Faris, Hossam ;
Aljarah, Ibrahim .
APPLIED INTELLIGENCE, 2018, 48 (04) :805-820
[33]  
Mohammadi N, 2017, MINERAL RESOURCES TO DISCOVER, VOLS 1-4, P1031
[34]   Supply chain network operations management of a blood banking system with cost and risk minimization [J].
Anna Nagurney ;
Amir H. Masoumi ;
Min Yu .
Computational Management Science, 2012, 9 (2) :205-231
[35]   A fuzzy vendor managed inventory of multi-item economic order quantity model under shortage: An ant colony optimization algorithm [J].
Nia, Ali Roozbeh ;
Far, Mohammad Hemmati ;
Niaki, Seyed Taghi Akhavan .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 155 :259-271
[36]  
Pasandideh SHR, 2018, ARXIV180108485
[37]   A multi-objective improved teaching-learning based optimization algorithm (MO-ITLBO) [J].
Patel, Vivek K. ;
Savsani, Vimal J. .
INFORMATION SCIENCES, 2016, 357 :182-200
[38]  
Pholdee N, 2017, INT J VEHICLE DES, V73, P20
[39]   Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions [J].
Rahmani, Donya .
ANNALS OF OPERATIONS RESEARCH, 2019, 283 (1-2) :613-641
[40]   Blood supply chain network design under uncertainties in supply and demand considering social aspects [J].
Ramezanian, Reza ;
Behboodi, Zahra .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2017, 104 :69-82