The　global　trend　for　industries　to　comprehensively　improve　the　utilization　of　resources　has　attracted　great　attention　from　many　researchers.　Industry　managers　are　increasingly　optimizing　their　production　strategies　under　time-of-use　(TOU)　electricity　tariffs　to　reduce　energy　consumption　since　it　accounts　for　the　majority　of　total　production　costs.　This　paper　investigates　the　single-machine　scheduling　problem　with　release　dates　under　TOU　tariffs.　The　key　issue　is　to　assign　a　group　of　jobs　with　different　release　dates　to　a　single　machine　to　minimize　the　total　electricity　cost.　To　solve　the　problem,　a　mixed-integer　linear　programming　(MILP)　model　based　on　time-indexed　formulation　(TI-MILP)　is　proposed.　By　preliminary　experiments,　we　find　TI-MILP　model　is　not　efficient　enough.　Therefore,　to　more　efficiently　solve　the　problem,　a　period-based　MILP　(P-MILP)　model　is　developed.　Finally,　extensive　experimental　results　demonstrate　that　i)　the　proposed　models　can　save　about　25%　on　total　electricity　cost　compared　with　the　existing　empirical　scheduling　method,　and　ii)　P-MILP　model　outperforms　TI-MILP　model　in　terms　of　computational　efficiency　and　problem　scale.　©　2022　IEEE.