Aiming　at　the　distribution　efficiency　and　cost　of　cold　chain　logistics　of　fresh　products,　a　solution　to　the　location-path　optimization　problem　of　green　cold　chain　logistics　using　an　improved　genetic　algorithm　from　the　perspective　of　low-carbon　environmental　protection　is　proposed.　First,　considering　transportation　costs,　fixed　costs,　refrigeration　costs,　and　time　penalty　costs,　increase　carbon　emission　costs　and　cargo　damage　costs　to　build　a　cold　chain　logistics　model.　Then,　combining　the　specific　model　of　the　optimization　problem　to　improve　the　genetic　algorithm,　including　the　coding　method,　genetic　operator　and　fitness　function,　etc.,　the　linear　adaptive　cross-mutation　strategy　is　introduced　to　dynamically　adjust　the　genetic　operator.　Finally,　the　improved　genetic　algorithm　is　used　to　solve　the　cold　chain　logistics　optimization　problem　to　effectively　reduce　carbon　emissions　and　cost　in　the　cold　chain　distribution　process.　Using　actual　cold　chain　logistics　and　distribution　data,　the　proposed　method　is　verified　based　on　the　Matlab　platform,　The　results　show　that　compared　with　other　methods,　the　proposed　method　accelerates　the　convergence　speed,　reduces　the　distribution　cost,　and　realizes　a　low-carbon　economy.