Treffer: Generalized robust goal programming model.

• Propose a generalized robust goal programming model that surpasses previous models. • The model addresses uncertainty in both LHS and RHS coefficients simultaneously. • The model supports all types of goal functions and covers major uncertainty sets. • Propositions validate the effectiveness of the proposed model. • Demonstrate superior robustness of our model through three comparative examples. This study proposes a concise and generalized robust goal programming (RGP) model that simultaneously considers three types of goal functions – right-side penalties, left-side penalties, and both-side penalties – under uncertainties on both the left-hand side and right-hand side. It integrates common uncertainty sets for a comprehensive goal programming model. Experimental results reveal that our model consistently outperforms existing RGP models by incurring fewer penalties, demonstrating enhanced resilience and robustness. This advantage becomes evident when problem coefficients such as costs, profits, and human resource requirements deviate significantly from their default target levels due to real-world conditions. The proposed model not only extends the robustness of traditional goal programming and weighted fuzzy goal programming but also offers improved risk management across various practical scenarios. [ABSTRACT FROM AUTHOR]

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