This　study　presents　a　bi-objective　optimization　model　for　the　Green　Vehicle-Routing　Problem　in　cold　chain　logistics,　with　a　focus　on　symmetric　distance　matrices,　aiming　to　minimize　total　costs,　including　carbon　emissions,　while　maximizing　customer　satisfaction.　To　address　this　complex　challenge,　we　developed　a　Stage-Specific　Multi-Objective　Five-Element　Cycle　Optimization　algorithm　(MOFECO-SS),　which　dynamically　adjusts　optimization　strategies　across　different　stages　of　the　process,　thereby　enhancing　overall　efficiency.　Extensive　comparative　analyses　with　existing　algorithms　demonstrate　that　MOFECO-SS　consistently　outperforms　in　solving　the　multi-objective　optimization　model,　particularly　in　reducing　total　costs　and　carbon　emissions　while　maintaining　high　levels　of　customer　satisfaction.　The　symmetric　nature　of　the　distance　matrix　further　aids　in　achieving　balanced　and　optimized　route　planning.　The　results　highlight　that　MOFECO-SS　offers　decision-makers　flexible　route　planning　options　that　balance　cost　efficiency　with　environmental　sustainability,　ultimately　improving　the　effectiveness　of　cold　chain　logistics　operations.