Nowadays,　numerous　manufacturing　companies　are　striving　to　enhance　their　process　performance　by　leveraging　innovative　technologies　like　collaborative　robots.　This　paper　introduces　a　novel　Human-Robot　Collaboration　(HRC)　scheduling　problem,　motivated　by　an　industry-university　partnership　project.　For　simplicity,　this　scheduling　problem　is　named　＇ALB-HRC-FSS＇,　as　it　combines　elements　of　the　traditional　Assembly　Line　Balancing　(ALB)　and　Flow　Shop　Scheduling　(FSS)　problems　while　incorporating　the　concurrent　use　of　human　workers　and　collaborative　robots.　As　far　as　we　know,　this　study　is　among　the　first　to　link　the　ALB-HRC　with　the　FSS　from　a　mathematical　standpoint.　A　detailed　description　of　the　proposed　ALB-HRC-FSS　problem　setting　is　presented　by　numerical　examples,　disjunctive　graphs　and　Gantt　charts.　A　series　of　Mixed-Integer　Programming　(MIP)　models　are　developed　to　formulate　the　problem　interactively.　Due　to　computational　complexity,　a　hybrid　metaheuristic　algorithm　(i.e.,　a　combination　of　Memetic　Algorithm　and　Tabu　Search)　is　developed　to　solve　the　ALB-HRC-FSS　problem　effectively.　Computational　experiments　with　scenario-based　analysis　are　performed　to　verify　the　practicality　and　effectiveness　of　the　proposed　ALB-HRC-FSS　methodology.　As　the　ALB-HRC-FSS　integrates　the　strengths　of　three　research　domains　(i.e.,　assembly　line　balancing,　human-robot　collaboration　and　flow　shop　scheduling),　this　study　contributes　to　designing　a　more　holistic　industrial　system　for　reshaping　manufacturing　processes　in　the　context　of　Industry　5.0.　©　2025　Elsevier　Ltd