In　an　attempt　to　understand　the　impact　of　traffic　congestion　on　the　cost　and　risk　of　hazardous　waste　transportation,　a　route　traffic　congestion　index　is　introduced　in　this　paper,　and　a　double-objective　optimization　model　of　hazardous　waste　recovery　based　on　the　traffic　congestion　index　in　a　time-dependent　road　system　is　established.　The　formula　for　calculation　of　heuristic　factors　in　a　traditional　ant　colony　algorithm　is　also　improved,　and　the　improved　ant　colony　algorithm　is　used　to　solve　the　model.　Finally,　a　case　study　was　carried　out　on　hazardous　waste　recycling　in　an　environmental　protection　company.　The　results　show　that　different　departure　times　and　vehicle　usage　patterns　have　a　significant　impact　on　the　Pareto　optimal　solution　and　the　shortest　route　does　not　necessarily　involve　the　lowest　energy　consumption.　The　models　and　algorithms　proposed　in　this　paper　can　assist　in　the　development　of　more　efficient　scheduling　schemes.　©2019,　Editorial　Board　of　Journal　of　Beijing　University　of　Chemical　Technology　(Natural　Science　Edition).　All　right　reserved.