A multi-objective optimization approach for supply chain design of alum sludge-derived supplementary cementitious material AITranslate

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DOI：https://doi.org/10.1016/j.cscm.2022.e01156

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Highlights • The first model for multi-objective alum sludge-to-supplementary cementitious material supply chain design. • Objectives maximizing social benefit by quantifying job opportunities, greenhouse gas emission savings, and economic return. • Pareto-optimal solutions show trade-offs among multiple objectives. • A real case study in Australia is investigated to test the applicability and viability of the supply chain network design. Most alum sludge is disposed of in landfill sites in Australia, resulting in significant environmental pollution and management cost. Effective management of sludge in a more sustainable manner remains a critical social, environmental, and economic concern. To simultaneously solve the dilemma of sludge management, economic expenditure of disposal, greenhouse gas emissions, and social impacts, this study proposed a multi-objective model for supply chain design of alum sludge-derived supplementary cementitious material as a viable solution. This study identified and quantified the potential social benefit by considering different impacts of new working opportunities based on their type and location, optimized the greenhouse gas emission saving for the potential supply chain, and assessed the economic benefit of the optimal untapped supplementary cementitious material value chain. The viability and applicability of the model are demonstrated through a case study in Australia, where potential utilization paths for available alum sludge are valued. A set of Pareto-optimal solutions was generated using the ɛ-constraint method, and three compromise Pareto-optimal solutions showed a clear trade-off among three objectives. The result analysis of each single-objective optimization indicates that the maximum working opportunity brought by the proposed supply chain was over 3.6 million working hours. Besides, up to 5.5 billion tonnes of greenhouse gas emissions saving was reported when maximizing the environmental objective, and the maximum economic benefit in the form of net present value was over 200 million Australian dollars in simulated 20 years. The Pareto-optimal solutions report a trade-off among three objectives, and two compromised solutions are proposed based on the level of objective values.