Green-blood supply chain network design: Robust optimization, bounded objective function &amp; Lagrangian relaxation

Heidari-Fathian, Hassan; Pasandideh, Seyed Hamid Reza

doi:10.1016/j.cie.2018.05.051

Cited by 86 publications

(36 citation statements)

References 57 publications

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“…With the mathematical model they propose, performance criteria such as cost efficiency, product absence and product excess are improved. Heidari-Fathian and Pasandideh ( 2018 ) work on green blood supply chain design and propose a Lagrange relaxation approach to solve the mixed-integer mathematical model they propose. Eskandari-Khanghahi et al ( 2018 ) propose a multi-objective stochastic optimization model for a sustainable blood supply chain design.…”

Section: Literature Surveymentioning

confidence: 99%

Re-design of a blood supply chain organization with mobile units

2021

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This research analyses the re-organization of a blood supply chain organization. Blood supply chain network design is a hard problem. Uncertainties of the blood supply and demand, perishability of blood over time and compatibility of blood types are some factors that make the problem difficult. This paper presents a novel multi-objective mixed-integer location-allocation model for a blood supply chain design problem. Unlike many studies on blood supply chain design in the literature, supply chain network consisting of mobile and permanent units is planned together effectively with our mixed-integer programming model. Multi-objective structure of the model minimizes distances between the blood supply chain elements and the length of the mobile unit routes. The objectives are prioritized by experts using the Analytical Hierarchical Process. Finally, the model is implemented on a real life case study using real data from the Eastern Anatolia region of Turkey for various supply demand scenarios. The solutions offered by the model are compared with the current situation in the region. It is shown that the proposed model gives at least %25 more effective solutions. Moreover, sensitivity analysis on the budget constraint is conducted, and robustness of the model is empirically illustrated.

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Section: Literature Surveymentioning

confidence: 99%

Re-design of a blood supply chain organization with mobile units

2021

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“…Ghorbani et al [27] focused on the multi-objective problem with the objectives of recycling cost, rate of waste generated by reactors, and material recovery time for recyclable products. Heidari-Fathian and Pasandideh [28] proposed a multi-objective model for organ transplant transportation network design with the consideration of cost, lead time, and waiting time in queue. Sweetapple et al [29] investigated the objectives of GHG emission, effluent quality, and operational cost.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Ending inventory level of each manufacturer and holding capacity is given in Equations (26) and (27). Safety stock of manufacturer is provided in Equation (28). Inventory of the distributors and holding capacity of each distributor are shown in Equations (29) and (30).…”

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confidence: 99%

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

et al. 2020

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This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in the model. The priority index quantifies the qualitative social aspects, such as coordination, trust, behavior, and long-term relationships among the stakeholders. In a multi-echelon supply chain, the performance of distributor/retailer is affected by the performance of supplier/distributor. The priority index measures the relative performance index of each player within the supply chain. The maximization of priority index ensures the achievement of social sustainability in the supply chain. Moreover, to model cost uncertainty, a time series integrated regression fuzzy method is developed. This research comprises of three phases. In the first phase, a mixed-integer multi-objective mathematical model while considering the cost uncertainty has been formulated. In order to determine the parameters for priority index objective function, a two-phase fuzzy inference process is used and the rest of the objectives (cost and GHG) have been modeled mathematically. The second phase involves the development of solution methodology. In this phase, to solve the mathematical model, a modified interactive multi-objective fuzzy programming has been employed that incorporates experts’ preferences for objective satisfaction based on their experiences. Finally, in the third phase, a case study of the supply chain of surgical instruments is presented as an example. The results of the case provide optimal flow of products from suppliers to hospitals and the optimal sequence of the visits of different vehicle types that minimize total cost, GHG emissions, and maximizes the priority index.

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“…They have implemented the proposed model in the mushroom industry, improving the company's profits by 11% and environmental impacts by 28%. Heidari and Pasandideh [29] have presented a mixed integer linear model for a green blood supply chain. They have treated the demand and supply of blood with uncertainty and developed the problem by using robust stochastic programming.…”

Section: Literature Reviewmentioning

confidence: 99%

Green closed-loop supply chain network design with stochastic demand: a new accelerated benders decomposition method

Abad

Pasandideh

2020

Scientia Iranica

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Changing the structure of supply chains to move towards less polluting industries and better performance has attracted many researchers in recent studies. Design of such networks is a process associated with uncertainties and control of the uncertainties during decision-making is of particular importance. In this paper, a two-stage stochastic programming model was presented for the design of a green closed-loop supply chain network. In order to reach the environmental goals, an upper bound of emission capability that helps governments and industries to control greenhouse gas emissions was considered. During the reverse logistics of this supply chain, waste materials are returned to the forward flow by the disassembly centers. To control the uncertainty of strategic decisions, demand and the upper bound of emission capacity with three possible scenarios is considered. To solve the model, a new accelerated Benders decomposition algorithm along with Pareto-Optimal-Cut was used. The efficiency of the proposed algorithm was compared with the regular Benders algorithm. The effect of different numerical values of parameters and probabilities of scenarios on the total cost was also examined.

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Green-blood supply chain network design: Robust optimization, bounded objective function & Lagrangian relaxation

Cited by 86 publications

References 57 publications

Re-design of a blood supply chain organization with mobile units

Re-design of a blood supply chain organization with mobile units

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

Green closed-loop supply chain network design with stochastic demand: a new accelerated benders decomposition method

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