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Designing pharmaceutical supply chain networks with perishable items considering congestion

Abstract

Increasing competition among various companies has led supply chain managers to devise ways to reduce costs and production times. An important branch of the supply chain, namely the pharmaceutical supply chain network, which plays a significant role in people's lives, is considered in this paper. When it comes to human life, time and accuracy are the most important factors. In this paper, a multi-objective stochastic model is developed to reduce the time of delivering drugs to patients and minimize operating costs of the supply chain, considering congestion in production centers and scheduling jobs in flexible flow shop systems. Reducing greenhouse gas emissions is also addressed in this research. Two multi-objective methods, LP-metric and goal attainment, are used to solve the proposed multi-objective model. Finally, to illustrate the performance of the proposed model, several numerical test problems from small to a large extent are solved with a detailed sensitivity analysis. Through analyzing the computational results, confliction among objective functions is analyzed. Moreover, it is concluded that LP-metric outperforms the goal attainment approach profoundly by comparing two solution approaches.

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Correspondence to Ali Ghodratnama.

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Appendix

Appendix

This section includes the indices used to develop our mathematical model. Due to a large number of indices, we organized indices into the following three categories:

  • Supply chain network

  • Scheduling and sequencing

  • Queues formed in plants

Supply chain network

Indices, which are related to the supply chain network, as follows:

$$ i \in \left\{ {1,2,...,IT} \right\}\;\;{\text{Supplier}} $$
$$ j \in \left\{ {1,2,...,JT} \right\}\;\;{\text{Producer}} $$
$$ k,k^{^{\prime}} \in \left\{ {1,2,...,KT} \right\}\;\;{\text{DC}} $$
$$ l \in \left\{ {1,2,...,LT} \right\}\;\;{\text{Customer}} $$
$$ p \in \left\{ {1,2,...,PT} \right\}\;\;{\text{Product}} $$
$$ h,h^{^{\prime}} \in \left\{ {1,2,...,HT} \right\}\;\;{\text{Transportation}}\;{\text{mode}} $$
$$ t \in \left\{ {1,2,...,TT} \right\}\;\;{\text{Time}}\;{\text{period}} $$
$$ r \in \left\{ {1,2,...,RT} \right\}\;\;{\text{Production}}\;{\text{time}}\;{\text{period}} $$
$$ e \in \left\{ {1,2,...,ET} \right\}\;\;{\text{Delivery}}\;{\text{time}}\;{\text{period}} $$

Scheduling and sequencing

Indices, which are related to the scheduling and sequencing issue, as follows:

$$ s \in \left\{ {1,2,...,ST} \right\}\;\;{\text{Stages}} $$
$$ c \in \left\{ {1,2,...,CT} \right\}\;\;{\text{Machine}} $$

Queues in production centers

Indices, which are related to the queues in plants issue, as follows:

$$ b,b^{^{\prime}} \in \left\{ {1,...,BT} \right\}\;\;{\text{Batch}} $$

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Rekabi, S., Ghodratnama, A. & Azaron, A. Designing pharmaceutical supply chain networks with perishable items considering congestion. Oper Res Int J (2021). https://doi.org/10.1007/s12351-021-00674-x

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Keywords

  • Supply chain management
  • Queueing systems
  • Flexible flow systems
  • Green supply chains