Multi-objective optimization (MOO) is widely applied in sustainability problems where several objectives must be accounted for in the analysis. Unfortunately, its complexity grows with the number of objectives, which hampers its practical use. In this paper, we simplify MOO problems via their combination with multi-attribute decision-making (MADM) methods. The approach identifies a unique Pareto solution of the MOO problem, which best reflects the decision-makers’ preferences, by using weighting factors generated via four well-known MADM methods: SWING, SMART, AHP and TRADE OFF. The capabilities of this approach are illustrated through its application to the design and planning of a sugar/ethanol supply chain using questionnaires filled in by academic experts in the problem. We find that the weights obtained using MADM algorithms may well differ from the ones given by standard life-cycle assessment methods employed in systems engineering problems. Overall, our approach simplifies the MOO problem by identifying solutions consistent with the decision-makers’ preferences and by providing valuable insight on how these preferences are articulated in practice.

多目标优化（MOO）广泛应用于可持续性问题，其中在分析中必须考虑多个目标。不幸的是，它的复杂性随目标数量的增加而增加，这妨碍了它的实际使用。在本文中，我们通过将MOO问题与多属性决策方法（MADM）相结合来简化MOO问题。该方法通过使用通过四种著名的MADM方法（SWING，SMART，AHP和TRADE OFF）生成的加权因子，确定了MOO问题的独特的Pareto解决方案，该解决方案最能反映决策者的偏好。通过使用由问题专家填写的调查表将其应用于糖/乙醇供应链的设计和规划，可以说明这种方法的功能。我们发现，使用MADM算法获得的权重可能与系统工程问题中采用的标准生命周期评估方法给出的权重完全不同。总体而言，我们的方法通过识别与决策者的偏好一致的解决方案，并通过提供关于实践中如何表达这些偏好的宝贵见解，从而简化了MOO问题。