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

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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
  • Publish Date: 21 September 2020

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