This　paper　investigates　a　real　life　bi-objective　hybrid　flow　shop　scheduling　problem　in　an　energy-intensive　manufacturing　system,　in　which　glass　is　produced　successively　in　cutting,　printing　and　tempering　stages.　The　problem　aims　to　simultaneously　optimize　makespan　and　the　total　electricity　cost　under　a　time-of-use　electricity　pricing　policy.　The　glass　production　has　to　respect　the　following　environments:　(i)　the　cutting　and　printing　operations　are　processed　in　parallel　machine　environments;　(ii)　the　tempering　operation　is　processed　on　a　batch　machine;　(iii)　machine　eligibility　and　setup　time　have　to　be　considered　in　the　cutting　and　printing　stages;　(iv)　the　whole　manufacturing　system　is　under　a　time-of-use　electricity　pricing　policy.　For　the　problem,　an　integer　programming　model　is　firstly　proposed　and　shown　to　be　strongly　NP-hard.　Then　a　model-based　heuristic　is　adopted　and　a　bi-objective　differential　evolution　algorithm　(BODE)　is　devised　based　on　problem　features.　Computational　experiments　on　randomly　generated　instances　demonstrated　that　the　BODE　outperforms　the　model-based　heuristic　in　terms　of　computation　time　and　solution　quality.　Moreover,　with　mild　increase　on　computation　burden,　the　BODE　significantly　outperforms　the　classic　NSGA　II　in　terms　of　solution　quality.　(C)　2018　Elsevier　Ltd.　All　rights　reserved.