Over the years, the global supply chain has evolved into a more extensive interconnected complex network with multiple suppliers, manufacturers, and customers. Since environmental issues have become a burning question in recent years, the focus has shifted to attaining sustainability in supply chain management. The green supply chain or sustainable network is a concept to reduce environmental impacts in the life cycle of a product. However, green supply chain management is often challenged with additional operating costs and difficulty monitoring the implications within the complex network system. Additionally, many stakeholders are unaware of the importance of sustainability analysis, which eventually complicates adopting green cultures in actual applications. Since green supply chain management deals with multiple aspects, such as cost and carbon emission, the multiobjective optimization method is widely used to evaluate supply chain performance. This paper intensively reviews the state-of-the-art literature on applying multiobjective optimization techniques in green supply chain management. The study highlights aspects of green supply chain structures, model formulation techniques considering multiple objectives simultaneously, and solution methods for multiobjective optimization problems. Finally, a conclusion is drawn with the scope of the potential research opportunities for integrating economic and environmental considerations in sustainable supply chain management practice.

The secure and dependable functioning of pipeline infrastructure systems is pivotal for transporting vital energy resources during this transition era towards a more sustainable energy future. This paper presents a novel quantitative approach for assessing sustainability risk in pipeline infrastructure systems and provides insights for holistic sustainability design in pipeline operations. The proposed methodology introduces a comprehensive framework for quantifying sustainability risk by integrating probabilities of failure and cumulative consequences from social, environmental, and economic dimensions that impact pipeline integrity. Real-world pipeline incident data were employed to identify the main causes of pipeline incidents like corrosion failure, equipment malfunction, and excavation damage. The consequences arising from these incidents are categorized to measure the cumulative consequences of sustainability risk. By quantifying sustainability risk, operators of pipeline infrastructure systems can strategically mitigate and manage potential disruptions affecting long-term sustainability incentives. In doing so, the proposed approach significantly bolsters the vital role of pipeline infrastructure systems in fostering sustainable energy transportation, yielding substantial benefits for global communities and economies.

Background: The corn supply chain is vital for food security and economic stability regionally and globally. This study integrates sustainable supply chain management with location optimization to address trade-offs from climate change, economic viability, and environmental impact while assuming the constant social obligation inherent in the supply chain structure. Methods: This study employs a mixed-integer programming (MIP) framework to optimize facility locations in North Dakota, including corn production zones as suppliers and ethanol plants as consumers. Primary objectives include cost minimization and greenhouse gas reduction, enabling the prioritization of economic or environmental goals as per organizational strategies and regulations. This approach ultimately maximizes resource utilization by ensuring efficient production and distribution practices. Results: The case study results highlight the optimal selection of 20 out of 30 corn production zones to meet statewide ethanol plant demand efficiently. Using compressed natural gas (CNG) instead of diesel could potentially save USD 2 million annually and cut carbon emissions by up to 1148 thousand tons per year, demonstrating meaningful progress toward economic and environmental sustainability within the supply network. Conclusions: The presented work offers a systematic methodology for designing sustainable supply chains for various agricultural products, aligning with the broader goal of promoting sustainability and resilience for efficient agricultural production and distribution systems.

This study introduces a quantitative approach to evaluating the resilience of oil pipeline systems against various natural and physical disruptions. Resilience is increasingly essential in critical infrastructure to ensure continuous operations and minimize disruption impacts. However, existing quantitative methods often need specific time-dependent data, making measuring resilience in pipeline infrastructure challenging. To address this gap, this paper proposed a comprehensive framework by integrating the existing incident database with key features of assessing failure probabilities based on historical events and developing multi-event resilience indicators based on system performance under various disruptions. The methodology employs event tree analysis to quantify the probabilities of multiple failure scenarios and their impact on pipeline operations and recovery efforts. The practical application of the proposed approach was demonstrated using real-world oil pipeline incident data from across the United States, covering the period from 2010 to 2022. The focus was on multiple event scenarios involving pipeline disruptions, followed by shutdowns, examining how these events collectively impact pipeline resilience. The results indicate that corrosion failure, equipment failure, and natural hazard damage significantly impact oil pipeline resilience. Corrosion and equipment failures affect resilience primarily due to their frequency, while natural hazard damage, despite its lower occurrence rate, is more unpredictable and often requires more frequent shutdowns. Understanding these failure causes and their impacts is essential for enhancing the resilience and sustainable operation of oil pipeline systems.