Sustainable supply chain management for perishable products is a complex issue requiring balance between economic performance, environmental impact, and social responsibility. This study conducts a systematic literature review of multi-objective optimization methods used in designing sustainable supply chains for perishable products. The main objective is to identify and analyze various optimization methods such as Lexicographic Goal Programming (LGP), Multi-Choice Goal Programming (MCGP), Weighted Goal Programming (WGP), and Augmented ε-constraint (AEC) in the context of perishable product supply chains. Using the PRISMA method, 146 references were identified from Scopus and Google Scholar databases, which were then filtered down to 11 final articles for in-depth analysis. The results show that each method has distinct characteristics and advantages - LGP is effective for hierarchical optimization with clear priorities, MCGP provides flexibility in target selection, WGP enables balanced optimization through weighting, while AEC produces more robust solutions for complex problems. These findings provide valuable insights for practitioners and researchers in selecting appropriate optimization methods for designing sustainable supply chains for perishable products. This study also identifies knowledge gaps and future research opportunities in sustainable supply chain optimization.