An integrated mathematical model of production and distribution planning for radiopharmaceutical products (Case study: Pars isotope company)

Document Type : Research/ Original/ Regular Article

Authors

1 M.S. Student of Industrial Engineering, Department of Chemical and Industrial Engineering, Mazandaran University of Science and Technology, Behshahr

2 Faculty of Chemical and Industrial Engineering, Mazandaran University of Science and Technology, Behshahr, Iran,

3 Assistant Professor of Industrial Engineering Department of Chemical and Industrial Engineering, Mazandaran University of Science and Technology, Behshahr, Iran

Abstract

Production and Distribution planning of radiopharmaceutical products aroused as a major concern due to the increasing the number of cancer patients and deaths. Radiopharmaceuticals are not only used for diagnosing process but also utilized for evaluating the function of body tissue and treatment. Shorter half-life of the radiopharmaceutical products rather than deteriorated products have complicated its production and distribution decision problems. In this paper an integrated mathematical programming has been developed for optimizing production, distribution, and injection planning of the radiopharmaceutical products. The proposed model aims to maximize production profitability through decreasing the production costs. Also the trade-off between production cost (depend on the time it takes to bombard raw materials) and the deviation time between production and injection times have been considered according to the nature of radiopharmaceutical production process in real-world problems. Furthermore an injection time window is considered for customer shown the preference of the customer to receive the radiopharmaceutical. The validity and efficiency of the proposed model were analyzed by implementation in a case study. The results show that the integrated model of production and distribution planning can not only decrease the cost of production but also increase the satisfaction level of the customers.

Keywords

References

[1]w.h.O."cancer."https://www.who.int/news-room/fact-sheets/detail/cancer
[2]P. Ghare, "A model for an exponentially decaying inventory," J. ind. Engng, vol. 14, pp. 238-243, 1963.
[3]F.Raafat,"Survey of literature on continuously deteriorating inventory models," Journal of the Operational Research society, vol. 42, no. 1, pp. 27-37, 1991.
[4]H.-M. Wee, "Economic production lot size model for deteriorating items with partial back-ordering," Computers & Industrial Engineering, vol. 24, no. 3, pp. 449-458, 1993.
[5]G. C. Lin, D. E. Kroll, and C. Lin, "Determining a common production cycle time for an economic lot scheduling problem with deteriorating items," European Journal of Operational Research, vol. 173, no. 2, pp. 669-682, 2006.
[6]J. Pahl, S. Voß, and D. Woodruff, "Production planning with deterioration constraints: a survey," in 19th International Conference on Production Research, 2007, p. 6.
[7]M. E. Ferguson and O. Koenigsberg, "How should a firm manage deteriorating inventory?," Production and Operations Management, vol. 16, no. 3, pp. 306-321, 2007.
[8]J. Pahl and S. Voß, "Integrating deterioration and lifetime constraints in production and supply chain planning: A survey," European Journal of Operational Research, vol. 238, no. 3, pp. 654-674, 2014.
[9]X. Li, Y. Ouyang, and F. Peng, "A supporting station model for reliable infrastructure location design under interdependent disruptions," Procedia-Social and Behavioral Sciences, vol. 80, pp. 25-40, 2013.
[10]S.K.Goyal and B. C. Giri, "Recent trends in modeling of deteriorating inventory," European Journal of operational research, vol. 134, no. 1, pp. 1-16, 2001.
[11]X. Ma, S. Wang, and Q. Bai, "Coordination of production scheduling and vehicle routing problems for perishable food products," International Journal of Internet Manufacturing and Services, vol. 6, no. 1, pp. 79-96, 2019.
[12]I. Radioisotopes and R. S. No, "Cyclotron Produced Radionuclides: Guidance on Facility Design an
 
Production of [18F] Fluorodeoxyglucose (FDG)
[13]C. A. Ullrich, "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, vol. 227, no. 1, pp. 152-165, 2013.
[14]Y.-C. Chang and C.-Y. Lee, "Machine scheduling with job delivery coordination," European Journal of Operational Research, vol. 158, no. 2, pp. 470-487, 2004.
[15]C.-L. Li, G. Vairaktarakis, and C.-Y. Lee, "Machine scheduling with deliveries to multiple customer locations," European Journal of Operational Research, vol. 164, no. 1, pp. 39-51, 2005.
[16]P. Amorim, M. Belo-Filho, F. M. B. d. Toledo, C. Almeder, and B. Almada-Lobo, "Lot sizing versus batching in the production and distribution planning of perishable goods," International Journal of Production Economics, vol. 146, no. 1, pp. 208-218, 2013.
[17]S. E. Kesen and T. Bektaş, "Integrated Production Scheduling and Distribution Planning with Time Windows," in Lean and Green Supply Chain Management: Springer, 2019, pp. 231-252.
[18]J. Lee, B.-I. Kim, A. L. Johnson, and K. Lee, "The nuclear medicine production and delivery problem," European Journal of Operational Research, vol. 236, no. 2, pp. 461-472, 2014.
[19]P. Devapriya, W. Ferrell, and N. Geismar, "Integrated production and distribution scheduling with a perishable product," European Journal of Operational Research, vol. 259, no. 3, pp. 906-916, 2017.
[20]C. Wang, C. Liu, Z.-h. Zhang, and L. Zheng, "Minimizing the total completion time for parallel machine scheduling with job splitting and learning," Computers & Industrial Engineering, vol. 97, pp. 170-182, 2016.
[21]J. Correa, V. Verdugo, and J. Verschae, "Splitting versus setup trade-offs for scheduling to minimize weighted completion time," Operations Research Letters, vol. 44, no. 4, pp. 469-473, 2016.
[22]T. Park, T. Lee, and C. O. Kim, "Due-date scheduling on parallel machines with job splitting and sequence-dependent major/minor setup times," The International Journal of Advanced Manufacturing Technology, vol. 59, no. 1, pp. 325-333, 2012.
Supply Chain Management
Volume 22, Issue 67
October 2020
Pages 80-92

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History

  • Receive Date: 09 May 2020
  • Revise Date: 22 July 2020
  • Accept Date: 11 August 2020

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