This　paper　considers　the　integrated　scheduling　problem　of　production　and　delivery　on　parallel　batch　processing　machines　with　non-identical　capacities　in　different　locations　in　cloud　manufacturing.　It　is　assumed　that　the　jobs　have　arbitrary　release　times,　different　job　sizes,　unequal　processing　times,　and　unique　information　of　customers　submitting　jobs.　The　service　completion　time　of　a　job　is　the　sum　of　the　production　completion　time　and　the　delivery　duration.　The　objective　of　the　studied　problem　is　to　minimize　the　total　service　completion　time.　A　mixed-integer　programming　(MIP)　model　is　presented　to　solve　this　problem.　Since　the　problem　is　NP-hard,　an　efficient　heuristic　algorithm　and　an　improved　particle　swarm　optimization　algorithm　are　proposed.　The　two　proposed　algorithms　are　compared　with　several　state-of-the-art　algorithms　and　the　commercial　optimization　solver　(Gurobi)　through　extensive　experiments,　verifying　the　effectiveness　of　the　proposed　algorithms.　©　2022　Elsevier　Ltd