In　the　process　of　sewage　treatment,　energy　consumption　and　effluent　quality　are　a　pair　of　contradictory　indicators.　In　order　to　find　the　optimal　solution　of　these　two　objectives,　this　paper　improves　multi-objective　evolutionary　algorithm　based　on　decomposition　(MOEA/D)　that　expects　even　distribution　with　fewer　evolution　times　for　an　approximate　Pareto　front.　This　algorithm　aims　at　the　new　solution　by　using　the　MOEA/D　algorithm　each　time,　finds　the　most　suitable　sub-problem　of　the　new　solution　from　all　the　sub-problems,　and　carries　out　replacement　of　the　population　within　its　neighborhood,　based　on　the　original　sub-problem.　Secondary　search　improves　the　utilization　of　the　child　generation　and　finds　the　approximate　Pareto　front　in　the　optimization　problem　with　fewer　iterations.　Experiments　show　that　the　algorithm　significantly　reduces　the　number　of　steps　to　find　the　Pareto　front,　which　results　in　a　significant　increase　in　the　performance　of　the　MOEA/D　algorithm　and　achieves　the　goal　of　optimization　in　the　wastewater　treatment　process.　©　2020,　Editorial　Department　of　Control　Theory　&　Applications　South　China　University　of　Technology.　All　right　reserved.