Two-Stage Stochastic Program for Supply Chain Network Design under Facility Disruptions

Kungwalsong, Kanokporn; Cheng, Chen-Yang; Yuangyai, Chumpol; Janjarassuk, Udom

doi:10.3390/su13052596

Cited by 13 publications

(9 citation statements)

References 34 publications

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“…This integrability may suppose a correct maintenance of the database involving an updated inventory of animals on farm and the location of facilities, but also market prices, forecasts, and trucks at disposal. Other papers dealing with two-stage stochastic models in other supply chains facing similar questions [32,33].…”

Section: Discussionmentioning

confidence: 99%

Supply Chains: Planning the Transportation of Animals among Facilities

2023

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Pig supply chains conform differently depending on country; however, the industrial production of pig meat has led to an increasing specialization of agents taking part in the supply chain production. Nowadays, pigs are rarely produced in one single farm, the existence of specialized farms devoted to breeding, rearing, and fattening pigs being more common since this organization provides sanitary advantages against disease outbreaks. Management strategies such as batch management in sow and fattening farms add complexity to the production management. Pigs have to be transferred from facility to facility as they are growing and sent to the abattoir as soon as they reach commercial weight. All these stages involve either independent farmers or farmers integrated in some pig supply chain management organization operating with production contracts or cooperation agreements. This study presented the challenge of using a stochastic model for planning the transportation of animals among facilities in pig supply chains over time. The model provides an optimal schedule of transfers between farms, occupancy rate, and trucks involved. The integrality of several variables was relaxed, and further analysis was performed in view of inspecting the model behavior for achieving practical decision support. We demonstrated that we can achieve good enough results in few minutes and, so, practical use is feasible.

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Section: Discussionmentioning

confidence: 99%

Supply Chains: Planning the Transportation of Animals among Facilities

2023

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“…The Monte Carlo sampling technique is applied to construct a smaller sample average problem instead of solving the problem with all possible scenarios [40]. This approach is known as the Sample Average Approximation (SAA) method.…”

Section: Sample Average Approximation Methodsmentioning

confidence: 99%

“…Then, Haghjoo et al [39] have investigated the supply chain network design problem for blood supply by dealing with location-allocation decisions under disruption and facility uncertainty in a disaster situation. More recently, Kungwalsong et al [40] have addressed the logistics network design problem considering possible disruptions at facilities. Moreover, Tolooie et al [5] have solved a logistics network design problem under total disruption at a facility and uncertain demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a Resilient and Sustainable Logistics Network under Epidemic Disruptions and Demand Uncertainty

2021

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To face the new challenges caused by modern industry, logistics operations managers need to focus more on integrating sustainability goals, adapt to unexpected disruptions and find new strategies and models for logistics management. The COVID-19 pandemic has proven that unforeseen fragilities, negatively affecting the supply chain performance, can arise rapidly, and logistics systems may confront unprecedented vulnerabilities regarding network structure disruption and high demand fluctuations. The existing studies on a resilient logistics network design did not sufficiently consider sustainability aspects. In fact, they mainly addressed the independent planning of decision-making problems with economic objectives. To fill this research gap, this paper concentrates on the design of resilient and sustainable logistics networks under epidemic disruption and demand uncertainty. A two-stage stochastic mixed integer programming model is proposed to integrate key decisions of location–allocation, inventory and routing planning. Moreover, epidemic disruptions and demand uncertainty are incorporated through plausible scenarios using a Monte Carlo simulation. In addition, two resiliency strategies, namely, capacity augmentation and logistics collaboration, are included into the basic model in order to improve the resilience and the sustainability of a logistics chain network. Finally, numerical examples are presented to validate the proposed approach, evaluate the performance of the different design models and provide managerial insights. The obtained results show that the integration of two design strategies improves resilience and sustainability.

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“…Sustainability 2021, 13, x FOR PEER REVIEW 3 of 13 Kungwalsong et al in 2021 proposed two-stage scholastic programming for the supply chain network design [14]. Giuffrida and Mangiaracina studied the green supply chain network design and provided a comprehensive literature review in this field [15].…”

Section: Methodsmentioning

confidence: 99%

Sustainable Closed-Loop Mask Supply Chain Network Design Using Mathematical Modeling and a Fuzzy Multi-Objective Approach

et al. 2021

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The outbreak of the deadly coronavirus, which is increasing the number of victims every day, has created many changes in today’s world. The use of various masks is the most important social tool against this virus. Given the importance of rapid and quality supply of masks in the current situation, it is necessary to study supply chain in particular. In this research, the design of a closed chain supply chain network for different types of masks is assessed. The studied supply chain includes suppliers, manufacturers, distributors, and retailers in the forward flow and collection centers, separate centers, recycling centers, and disposal centers in the backward flow. In this regard, a multi-objective mathematical model with the objectives of increasing the total profit and reducing the total environmental impact, and maximizing social responsibility is presented. The optimization of this mathematical model has been done using a fuzzy optimization approach in GAMS software. The results of this study show that maximizing the total profit and minimizing the environmental effects and maximizing social responsibility are in contrast to each other. In addition, the sensitivity analysis indicated that the customers’ demand can affect all aspects of the sustainable supply chain simultaneously.

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Two-Stage Stochastic Program for Supply Chain Network Design under Facility Disruptions

Cited by 13 publications

References 34 publications

Supply Chains: Planning the Transportation of Animals among Facilities

Supply Chains: Planning the Transportation of Animals among Facilities

Designing a Resilient and Sustainable Logistics Network under Epidemic Disruptions and Demand Uncertainty

Sustainable Closed-Loop Mask Supply Chain Network Design Using Mathematical Modeling and a Fuzzy Multi-Objective Approach

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