In　this　paper,　an　integer　programming　model　is　developed　for　a　newly　addressed　coke　production　scheduling　problem,　in　which　two　typical　characteristics　are　considered:　(i)　The　transportation　of　raw　coal　by　a　vehicle　causes　a　batch　preprocessing;　(ii)　The　heating　of　raw　coal　by　closely　located　coke　ovens　may　extend　the　processing　times　of　cokes,　under　the　temperature　influence.　To　the　best　of　our　knowledge,　such　a　geographically　location-dependent　processing　time　has　not　been　studied.　The　purpose　is　to　minimize　the　completion　time　of　the　last　coke　among　all　ovens,　i.e.,　the　makespan.　Therefore,　the　problem　of　interest　can　be　viewed　as　a　parallel　machine　makespan　minimization　scheduling　problem,　featured　with　batch　preprocessings　and　location-dependent　processing　times.　For　this　NP-hard　problem,　a　problem-specific　genetic　algorithm　and　a　fast　heuristic　are　devised　to　enhance　the　computational　efficiency.　Experimental　results　on　330　randomly　generated　instances　show　the　effectiveness　and　efficiency　of　the　proposed　solution　methods.　©　2018