Logistic optimization of the blood delivery routing problem in the Lower Southern region of Thailand
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Abstract
This study discusses a blood delivery routing problem faced by a regional blood centre (RBC). The RBC meets the requests of 21 hospitals for blood and blood products. Each hospital can request product deliveries throughout the day, but the RBC has a cut-off time for its transportation round and manually designates a specific route for the transport van, which is available only during working hours. This vehicle routing problem operates under vehicle time restriction constraints. The aim of the research is to use a metaheuristic method to find the optimal transport route to deliver blood and blood products at minimal total cost. This paper proposes a novel hybrid metaheuristic method that combines the firefly algorithm (FA) as the main structure, a crossover operator in differential evolution (DE) and a new local search (NLS); is called the HFA+NLS algorithm. The exact solution of the mathematical model and current practice are used for comparisons of the quality of the solutions. Four existing algorithms are also employed to compare the search performance. The paired t-test is used to compare the means of the search performance measures of any two methods. Different sizes of problem are considered by generating a set of nine test instances (small, medium and large problems) and a real-world case study to verify the competitive performance of the proposed algorithm. The computational results reveal that the HFA+NLS algorithm has a superior performance to other methods in the number of test instances for which the optimal, or the best known, solution was successfully found. The HFA+NLS algorithm determines the best route for a blood transport van with a total blood transportation cost reduction of 66.46%.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
International Federation of Red Cross and Red Crescent Societies. Federation-wide databank and reporting system [Internet]. 2022 [cited 2022 Aug 11]. Available from: https://data.ifrc.org/FDRS/fdrs/national-societies.
Eskandari-Khanghahi M, Tavakkoli-Moghaddam R, Taleizadeh AA, Amin SH. Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty. Eng Appl Artif Intell. 2018;71:236-50.
Zahiri B, Torabi SA, Mohammadi M, Aghabegloo M. A multi-stage stochastic programming approach for blood supply chain planning. Comput Ind Eng. 2018;112:1-14.
Mousavi R, Salehi-Amiri A, Zahedi A, Hajiaghaei-Keshteli M. Designing a supply chain network for blood decomposition by utilizing social and environmental factor. Comput Ind Eng. 2021;160:107501.
Şahinyazan FG, Kara BY, Taner MR. Selective vehicle routing for a mobile blood donation system. Eur J Oper Res. 2015;245(1): 22-34.
Iswari T, Yu VF, Asih AMS. Simulated annealing for the blood pickup routing problem. Int J Inf Manag Sci. 2016;27(4):317-327.
Yu VF, Iswari T, Normasari NME, Asih AMS, Ting H. Simulated annealing with restart strategy for the blood pickup routing problem. IOP Conf Ser: Mater Sci Eng. 2018;337:012007.
Özener OÖ, Ekici A. Managing platelet supply through improved routing of blood collection vehicles. Comput Oper Res. 2018;98:113-26.
Haitam E, Najat R, Abouchabaka J. A vehicle routing problem for the collection of medical samples at home: case study of Morocco. Int J Adv Comput Sci Appl. 2021;12(4):345-51.
Karakoc M, Gunay M. Priority based vehicle routing for agile blood transportation between donor/client sites. 2017 International Conference on Computer Science and Engineering (UBMK); 2017 Oct 5-8; Antalya, Turkey. USA: IEEE; 2017. p. 795-9.
Liu R, Xie X, Augusto V, Rodriguez C. Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care. Eur J Oper Res. 2013;230(3):475-86.
Ganesh K, Narendran TT, Anbuudayasankar SP. Evolving cost–effective routing of vehicles for blood bank logistics. Int J Logist Syst Manag. 2014;17(4):381-415.
Rabbani M, Aghabegloo M, Farrokhi-Asl H. Solving a bi-objective mathematical programming model for bloodmobiles location routing problem. Int J Ind Eng Comput. 2017;8(1):19-32.
Lestari F, Rizky M, Umam MIH, Indriyani FF. Vehicle routing problem using sweep algorithm for determining distribution routes on blood transfusion unit. Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management; 2021 Sep 14-16; Surakarta, Indonesia. Southfield: IEOM Society International; 2021. p. 263-73.
Jafarkhan F, Yaghoubi S. An efficient solution method for the flexible and robust inventory-routing of red blood cells. Comput Ind Eng. 2018;117:191-206.
Ghasemi E, Bashiri M. A selective covering-inventory-routing problem to the location of bloodmobile to supply stochastic demand of blood. Int J Ind Eng Prod Res. 2018;29(2):147-58.
Mousazadeh S, Darestania SA. Modeling a production-inventory-routing problem of blood products using heuristic solution methods. J Intell Fuzzy Syst. 2019;37(4):5589-609.
Pathomsiri S, Sukhaboon P. Analysis and design of blood transportation in Bangkok metropolitan region a case study for the National Blood Center, Thai Red Cross Society. J Eng RMUTT. 2011;2:41-50. (In Thai)
Taweeugsornpun N, Raweewan M. Vehicle routing for blood product delivery. Panyapiwat J. 2017;9:230-45.
Sujaree K, Jirawongnuson S. Blood vehicle routing problem by hybrid cuckoo search algorithm. Kasem Bundit Eng J. 2018;8(2):206-26. (In Thai)
Banthao J, Jittamai P. Hybrid genetic algorithm for the location – routing problem with emergency referral. RMUTI J Sci Technol. 2018;11(1):1-16.
Intapan K, Kongkaew W, Suthummanon S, Mitundee S, Saranobphakhun S. A hybrid differential evolution for the blood routing problems: a case study of hospital cluster in Songkhla province. Thai J Oper Res. 2022;10(1):179-92.
Sethanan K, Pitakaso R. Differential evolution algorithms for scheduling raw milk transportation. Comput Electron Agric. 2016;121:245-59.
Song MX, Li JQ, Han YQ, Han YY, Liu LL, Sun Q. Metaheuristics for solving the vehicle routing problem with the time windows and energy consumption in cold chain logistics. Appl Soft Comput. 2022;95:106561.
Yesodha R, Amudha T. A bio-inspired approach: firefly algorithm for multi-depot vehicle routing problem with time windows. Comput Commun. 2022;190:48-56.
Boonyanusith W. The development of a blood allocation model for regional blood centers in Thailand [thesis]. Nakhon Ratchasima, Thailand: Suranaree University of Technology; 2016. (In Thai)
National Blood Centre. Daily blood needs of Thai hospitals nationwide. Songkhla: Regional Blood Centre 12th Songkhla, Thai Red Cross Society of Thailand; 2016. (In Thai)
Chantarasakul C. Storage and delivery of blood and blood components. J Hematol Transfus Med. 2008;18(3):243-8. (In Thai)
Yang XS. Firefly algorithm. In: Yang XS, editor. Nature-Inspired Metaheuristic Algorithms. UK: Luniver Press; 2008. p. 79-90.
Wang C, He J, Chen Y, Zou X. Influence of the binomial crossover on performance of evolutionary algorithms. arXiv: arXiv:2109.14195. 2021:1-21.
Kongkaew W, Wittayasilp S. A hybrid firefly algorithm to minimize total cost of earliness and tardiness in precast production scheduling. Thai J Oper Res. 2021;9(1):79-91. (In Thai)