supply chain management analyzing/modelling
Masoud Rabbani; Maryam Hemmati; mohammadReza mehregan
Abstract
Purpose: One of the biggest challenges of the 21st century is meeting the needs of the growing world population. The supply chain of perishable goods, including food, dairy products, medicines, and blood products, have recently received attention due to their impact on human life. In this article, the ...
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Purpose: One of the biggest challenges of the 21st century is meeting the needs of the growing world population. The supply chain of perishable goods, including food, dairy products, medicines, and blood products, have recently received attention due to their impact on human life. In this article, the design of a sustainable supply chain network for perishable items has been discussed. To optimize this supply chain, a multi-objective mixed integer linear programming (MILP) model has been developed to formulate the problem. Fixed deterioration rate (expiration date) is considered.
Methodology: To perform the research calculations, GAMS software and the combined method of Bander's analysis and Lagrange coefficient were used, and based on the data, results were obtained, and the relative weight of the stability of the solution (ω) was equal to 0.5 and the relative weight of the stability of the model was ( ω) equal to 5000 has been developed to meet the proposed objectives. These comparisons show that the presented network was robust in all performance objectives.
Findings: The results obtained from the combined method regarding the three objective functions defined for the main model show this fact. The results of the first iteration provide us with better answers compared to the other iterations.
Originality/Value: This research can be considered as one of the first optimization paper that presented a multi-level and multi-product-multi-period supply chain with uncertainty in the parameters in the dairy and pharmaceutical industries and the environmental costs of production and transportation, and sustainable social costs such as reported accidents and incidents, job satisfaction, safety, reduction of dispatch time and lost working days simultaneously with the economic dimension in management-related decisions. Allocation combines location and routing.
Location Modeling
Alireza Roshani; Mohammad Reza Gholamian; Mahsa Arabi
Abstract
Purpose: Due to the increasing complexity of uncertainty and its impact on the supply chain network, many researchers have resorted to coping approaches with data uncertainty. In addition, the occurrence of any disruption in the supply chain networks can cause irreparable damage. Therefore, adopting ...
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Purpose: Due to the increasing complexity of uncertainty and its impact on the supply chain network, many researchers have resorted to coping approaches with data uncertainty. In addition, the occurrence of any disruption in the supply chain networks can cause irreparable damage. Therefore, adopting appropriate strategies to increase the level of the supply chain network resilience toward any disruptive events seem to be necessary.Methodology: In this paper, a multi-objective, multi-period, and scenario-based mathematical model is presented in which objective functions of delivery time and total network cost are minimized, and to increase network resilience, non-resilience measures are also minimized. Furthermore, a Two-Stage Stochastic Programming (TSSP) approach has been utilized to overcome the uncertain nature of the input parameters. Goal programming has also been used to transform the model into a single-objective one.Findings: In order to prove the model's applicability, the real-world data of a case study of Mashhad has been implemented. Eventually, according to the validation and sensitivity analysis results, the proposed uncertain model has clear superiority over the deterministic model.Originality/Value: This paper presents a multi-objective linear mathematical model for designing the Pharmaceutical Supply Chain (PSC) network under the COVID-19 situation. Two indicators of time and resilience as optimization tools have been considered simultaneously.