Designing of sustainable reverse logistics network of drug based on digital transformation

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Designing of sustainable reverse logistics network of drug based on digital transformation

ارائه دهنده: Provider: Mehdi Alimohammadi

اساتید راهنما: Supervisors: Dr. Javad Behnamian

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: Dr. Vahid Khodakarami, Dr. Fariborz Jolai, Dr. Rashed Sahraeian

زمان و تاریخ ارائه: Time and date of presentation: 2024

مکان ارائه: Place of presentation: آمفی تئاتر دانشکده مهندسی

چکیده: Abstract: The complex and dynamic conditions of today’s world, most of which result from major advances in communication technology affected by digital transformation, necessitate revising and making fundamental amendments to the survival requirements of economic enterprises, especially the components of supply chains. Despite their drawbacks, current information technologies of this new digital era, as the main actors in this field, leave remarkable effects on increasing the quality and quantity level of communication and bring up a new definition to the whole concept. Reverse logistics is among the supply chain’s important components, playing a pivotal role in fulfilling the objectives of supply chain management, and it is affected by progress in information technology. Reverse logistics has been the subject of many researches during the past few decades. Meanwhile, applying information technologies to reverse logistics is of special note as it increases the quality and speed of information transfer, reduces communication services costs, and raises information-sharing processes’ security. In addition to, reverse logistics is critical in manufacturers’ access to a circular economy. Drug recycling has recently turned into a subject in need of special attention. This concept relates to alleviating the environmental burden due to waste pharmaceutical waste, supplying essential/strategic drugs, and developing the circular economy. The present study aims to design a governmental reverse logistics network to purchase and collect the citizens’ surplus (unused) drugs as a strategy to recycle drugs and dispose of pharmaceutical waste correctly and safely. The purchase of the citizens’ surplus drugs is done to resolve the adverse effects of the mismanagement of pharmaceutical waste, which could pose a potential danger to both humans and the environment. Meanwhile, owing to technology advancements, drug recycling and re-dispensing of unused drugs returned by one patient for use by another could translate into reality. The modeling procedure in this study is as follows: In the first section, surplus drugs are purchased from citizens by the government. Next, the objective function of the total cost of reverse logistics is calculated by designing a suitable mechanism through creating drug sorting, recycling, and elimination centers and defining the respective relations and constraints. Considering the Mixed Integer Nonlinear Programming (MINLP) nature of the problem, the Generalized Benders Decomposition (GBD) method is used to solve it. The drug recycling mechanism used in the second section is the same as that in the first section, except that drugs are purchased from citizens through outsourcing to Third-Party Reverse Logistics Provider companies. It is assumed that these companies use a three-channel platform based on digital transformation technologies to receive drug sales requests from citizens. Cloud computing and GIS are used in channels 1 and 2, and blockchain is used in the two areas of secure information exchange in the second section and the design of operations strategy in the third section. After developing a new demand function based on the Cobb-Douglas production function and drug pricing approach, a sustainable multi-objective bi-level model is designed and optimized in the second section. Finally, given the important role of third-party reverse logistics provider companies in the implementation of model 2, an operations strategy was designed for them in the third section. The numerical results of the first section indicate that the GBD is much more efficient in solving large-size problems than the CPLEX solver. Moreover, access to the Pareto front using the ε-constraint method in the numerical results of the second section shows that the basic price of the surplus drugs purchased by third-party reverse logistics provider companies and the price offered to these companies by the government are highly correlated. Given the considerable impact of these prices on the final reverse logistics cost, these prices need to be accurately selected and adjusted.

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