This　paper　aims　to　solve　the　problem　of　high　energy　consumption　in　forging　production　through　energy-saving　scheduling.　By　analyzing　the　flow　shop　characteristics　of　a　forging　workshop,　an　energy-efficient　hybrid　flow　shop　scheduling　problem　with　forging　tempering　(EEHFSP-FT)　is　proposed.　An　energy-efficient　scheduling　model　is　established　to　simultaneously　minimize　both　the　completion　time　and　energy　consumption.　In　the　scheduling　model,　constraints　such　as　heating　furnace　capacity,　required　forging　temperature,　and　required　quenching　temperature　are　taken　into　consideration.　An　energy-saving　strategy　of　heat　treatment　with　residual　forging　heat　is　adopted　to　address　the　problem　of　energy　underutilization　after　forging.　In　order　to　use　multi-objective　optimization　algorithms　to　solve　the　scheduling　problems　of　charging　and　machine　selection　in　forging　production,　encoding　and　decoding　rules　and　evolutionary　search　strategies　are　designed.　Finally,　a　case　study　on　the　flow　shop　of　an　automated　forging　center　is　analyzed.　The　validity　of　the　proposed　model　is　demonstrated　by　testing　cases　of　different　scales　in　conjunction　with　three　different　evolutionary　algorithms.　By　analyzing　the　performance　of　the　three　algorithms,　the　algorithm　suitable　for　solving　the　proposed　model　is　determined.