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    Optimization approaches for multiple conflicting objectives in sustainable green supply chain management
    (MDPI, 2022-10-01)
    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.
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    Location optimization strategies for corn production and distribution towards sustainable green supply chain
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-09-01)
    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.