During　the　last　decade,　we　are　witnessing　the　emergence　of　NFV　and　SDN　to　reduce　CAPEX　and　OPEX.　Under　the　SDN　paradigm　and　thanks　to　NFV,　a　service　can　be　swiftly　deployed　by　the　chaining　of　several　VNFs　forming　an　SFC　running　on　a　virtualized　infrastructure.　Nowadays,　there　are　still　quite　a　number　of　issues　related　to　SFCs,　among　them,　the　optimal　placement　of　SFC　components.　In　this　paper,　we　focused　on　the　variant　of　the　resource　allocation　cost　optimization　problem　of　VNF　placement　and　chaining　for　limited　resources　on　the　servers.　After　proving　that　the　problem　of　VNF　placement　is　NP-Hard　and　equivalent　to　the　multiple　knapsack　problem,　we　proposed　a　genetic　algorithm-based　meta-heuristic　to　solve　large　instance　of　our　VNF　placement　and　chaining　problem　variant.　Simulation　results　show　that　our　genetic　algorithms　are　efficient　since　they　reduce　the　SFC　mean　cost　and　improve　the　accepted　requests　ratio.