Traffic　congestion　is　a　daily　problem　facing　commuters　in　dense　cities.　This　problem　is　getting　worse　with　the　rapid　growth　of　cities＇　population　and　migration　from　rural　to　urban　areas.　Recently,　electric　dock-less　scooters　have　emerged　as　a　micro　mobility　mode　and　as　a　potential　solution　for　large　crowded　cities　with　limited　resources.　However,　a　question　of　how　to　charge　these　e-scooters　has　been　raised.　Many　e-scooter　companies　use　freelancers　to　charge　the　scooter　where　they　compete　to　collect　and　charge　the　e-scooters　at　their　homes.　This　competition　leads　the　chargers　to　travel　long　distances　to　collect　e-scooters.In　this　paper,　we　developed　a　mixed　integer　linear　programming　(MILP)　model　to　solve　the　E-Scooter-Chargers　Allocation　problem.　The　proposed　model　allocates　the　e-scooters　to　the　chargers　with　a　particular　emphasis　on　minimising　the　chargers＇　average　travelled　distance　to　collect　the　e-scooters.　Moreover,　we　modelled　the　charging　problem　as　a　game　between　two　sets　of　disjoint　players,　namely　e-scooters　and　chargers.　Then　we　adapted　the　college　admission　algorithm　(ACA)　to　solve　the　assignment　problem.　For　the　sake　of　comparison,　we　adapted　the　black　hole　optimiser　(BHO)　to　solve　this　problem.　The　experimental　results　showed　that　ACA　solutions　are　close　to　the　optimal　solutions　found　by　the　MILP.　Furthermore,　the　BHO　solutions　are　not　as　good　as　the　ACA　solutions.　So,　we　recommend　using　the　ACA　to　find　a　good　solution　for　very　large　instances　where　MILP　needs　a　long　time　to　find　the　optimal　solution.　©　2019　IEEE.