Design of a pharmaceutical supply chain network under uncertainty considering perishability and substitutability of products

Zahiri, Behzad; Jula, Payman; Tavakkoli–Moghaddam, Reza

doi:10.1016/j.ins.2017.09.046

Cited by 108 publications

(56 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“… Sánchez et al (2017) designed an optimization approach for modular neural network and proposed a firefly algorithm that the results of the firefly algorithm compared with hierarchical genetic algorithm. Zahiri et al (2018) provided a hierarchical mathematical model for designing a medicine supply chain network. Then, considering medicine perishable, stability, and the number of discounts on medicine purchases has been considered in their contributions.…”

Section: Literature Reviewmentioning

confidence: 99%

An integrated sustainable medical supply chain network during COVID-19

Goodarzian

Taleizadeh

Ghasemi

et al. 2021

Engineering Applications of Artificial Intelligence

180

View full text Add to dashboard Cite

Nowadays, in the pharmaceutical industry, a growing concern with sustainability has become a strict consideration during the COVID-19 pandemic. There is a lack of good mathematical models in the field. In this research, a production–distribution–inventory–allocation–location problem in the sustainable medical supply chain network is designed to fill this gap. Also, the distribution of medicines related to COVID-19 patients and the periods of production and delivery of medicine according to the perishability of some medicines are considered. In the model, a multi-objective, multi-level, multi-product, and multi-period problem for a sustainable medical supply chain network is designed. Three hybrid meta-heuristic algorithms, namely, ant colony optimization, fish swarm algorithm, and firefly algorithm are suggested, hybridized with variable neighborhood search to solve the sustainable medical supply chain network model. Response surface method is used to tune the parameters since meta-heuristic algorithms are sensitive to input parameters. Six assessment metrics were used to assess the quality of the obtained Pareto frontier by the meta-heuristic algorithms on the considered problems. A real case study is used and empirical results indicate the superiority of the hybrid fish swarm algorithm with variable neighborhood search.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

An integrated sustainable medical supply chain network during COVID-19

Goodarzian

Taleizadeh

Ghasemi

et al. 2021

Engineering Applications of Artificial Intelligence

180

View full text Add to dashboard Cite

show abstract

“…The presence of financial constraints significantly minimises the likelihood that organisations will implement improvement initiatives (D'Este et al, 2012;Guerrini et al, 2018) Awareness of improvement approaches Limited knowledge of improvement approaches; there is a shortage of expertise and methods (Greenhalgh et al, 2012) The lack of experience might lead to adoption of incorrect methods or the sub-optional use of the existing guidance (Bhakoo et al, 2012) Complexity of the healthcare sector Healthcare SCs has been chartacterised as more complex compared to SCs in other industries (Liddell et al, 2008;Papalexi et al, 2015) because of the impact on patient's health requiring an adequate and accurate medical supply (Mustaffa and Potter, 2009) The healthcare context sensitivity is the main factor that generates the complexity of the system (Kannampallil et al, 2011;Bam et al, 2017) Unpredictable healthcare complex system, including a number of diverse elements, whose relationships are not linear (Wilson and Holt, 2001;Zahiri et al, 2018) The high complexity of the system is influenced by the specific products and services delivered by healthcare organisations and the diversity of people working within this sector, their roles and actions (Greenhalgh et al, 2012) The institutional and regulatory pressures 4…”

Section: Literature Reviewmentioning

confidence: 99%

Key sources of operational inefficiency in the pharmaceutical supply chain

Papalexi

Bamford

Breen

2020

SCM

View full text Add to dashboard Cite

Purpose This study aims to explore the downstream pharmaceutical supply chain (PSC) and provides insight to the delivery process of medicines and associated operational inefficiencies. Design/methodology/approach An exploratory, qualitative approach was adopted to examine PSC inefficiency within two European contexts, namely, the UK and Greece. Data was gathered through interviews and a thematic analysis conducted to analyse the data and identify challenges faced by both supply chains(SCs). Findings The medicines delivery system needs to be enhanced in terms of quality, visibility, speed and cost to perform effectively. The findings demonstrated that although the healthcare SCs in the two European contexts have different operational structures, the results are in concordance with each other. Financial, communication, waste and complexity issues were the major concerns. Research limitations/implications To the knowledge this is the first study to examine aspects of the medicines SC via a cross-case analysis in the UK and Greece and extends the body of knowledge. A broader sample of responses is warranted to further validate these findings. Practical implications The study outputs can inform pharmacies’ strategic to instigate targeted improvement interventions. The implications of which may be extrapolated further to other European healthcare organisations. Originality/value This research contributes to the academic literature by adding further theoretical insights to SC strategy development, especially those that have been characterised as highly complex. The study identifies four key areas of intervention needed within this SC (in both countries) to promote higher level efficiencies and effectiveness.

show abstract

“…This work can also be extended by exploring other approaches for handling uncertainty such as: robust optimization, (Bairamzadeh et al [7]; Kara et al [31]), stochastic optimal control (Vinod et al [63]) and chance constraint optimization (Cheng et al [17]). This extension could include emerging areas of applications such as complex networks in alternative energy systems (Syahputra et al [60]; Lot et al [39]), social networks, gene networks (Youseph et al [67]) and pharmaceutical supply chain networks (Zahiri et al [68]…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System

Ganesan¹,

Vasant

Sanghvi³

et al. 2020

J. ADV. ENG. COMPUT.

View full text Add to dashboard Cite

Complex industrial systems often contain various uncertainties. Hence sophisticated fuzzy optimization (metaheuristics) techniques have become commonplace; and are currently indispensable for effective design, maintenance and operations of such systems. Unfortunately, such state-of-the-art techniques suffer several drawbacks when applied to largescale problems. In line of improving the performance of metaheuristics in those, this work proposes the fuzzy random matrix theory (RMT) as an add-on to the cuckoo search (CS) technique for solving the fuzzy large-scale multiobjective (MO) optimization problem; biofuel supply chain. The fuzzy biofuel supply chain problem accounts for uncertainties resulting from fluctuations in the annual electricity generation output of the biomass power plant [kWh/year]. The details of these investigations are presented and analyzed.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

show abstract

Design of a pharmaceutical supply chain network under uncertainty considering perishability and substitutability of products

Cited by 108 publications

References 39 publications

An integrated sustainable medical supply chain network during COVID-19

An integrated sustainable medical supply chain network during COVID-19

Key sources of operational inefficiency in the pharmaceutical supply chain

Random Matrix Generators for Optimizing a Fuzzy Biofuel Supply Chain System

Contact Info

Product

Resources

About