The　two-sided　assembly　line　becomes　very　popular　in　recent　years.　In　this　paper,　a　priority　rules-based　algorithmic　design　is　developed　for　optimizing　two-sided　assembly　line.　Five　elementary　rules　and　90　composite　rules　are　tested　on　the　benchmark　data　sets　and　their　performance　are　provided.　Two　enumerative　principles,　which　are　specific　to　two-sided　assembly　lines　are　proposed　to　enhance　the　performance　of　the　rules.　Further,　priority　rules　are　embedded　into　a　bounded　dynamic　programming　framework　to　form　a　deterministic　algorithm　where　the　use　of　a　bound　can　reduce　the　solution　space　as　the　algorithm　is　advanced　stage-by-stage.　These　approaches　offer　distinct　advantages　over　the　methods　proposed　in　the　literature,　such　as　less　fine-tuning　effort　and　more　stable　results.　Computational　results　show　that　the　novel　algorithm　can　generate　good　solutions　efficiently,　especially　in　large　sized　problems.　©　2017,　German　Academic　Society　for　Production　Engineering　(WGP).