Designing pharmaceutical supply chain networks with perishable items considering congestion

• Published in: Operational research Vol. 22; no. 4; pp. 4159 - 4219
• Main Authors: Rekabi, Shabnam, Ghodratnama, Ali, Azaron, Amir
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2022; Springer Nature B.V
• Subjects: Business and Management; Chain branching; Competitive advantage; Computational Intelligence; Congestion; Costs; Customers; Greenhouse gases; Inventory; Management Science; Mathematical analysis; Mathematical models; Operating costs; Operations Research; Operations Research/Decision Theory; Original Paper; Pharmaceutical industry; Pharmaceuticals; Production scheduling; Sensitivity analysis; Stochastic models; Supply chain management; Supply chains; Supply chain management; Flexible flow systems; Queueing systems; Green supply chains
• DOI: 10.1007/s12351-021-00674-x
• ISSN: 1109-2858

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.