Mobile　edge　computing　(MEC)　can　enhance　application　performance　effectively　by　offloading　computation　tasks　to　the　edge　server　hosting　corresponding　service　via　multi-access　wireless　networks.　However,　existing　service　placement　policies　are　more　based　on　the　assumption　that　application　services　can　be　used　without　restrictions,　while　ignoring　the　constraints　of　software　usage　by　license,　which　always　limits　user　number,　usage　periods,　etc.　To　address　these　challenges,　in　this　paper,　we　introduce　an　architecture　of　digital　twin-empowered　MEC　with　good　scalability　and　reliability,　formulate　an　optimal　problem　by　jointly　optimizing　task　offloading　and　service　placement,　which　takes　into　account　the　usage　number　limitation　for　one　service　at　the　same　time.　To　tackle　this　mix　integer　non-linear　programming　problem　(MINLP),　we　propose　a　DRL-based　algorithm　JTOSP　to　deal　with　high-dimensional　input　data　from　MEC　system,　and　to　cope　with　the　stochastic　nature　in　dynamic　underlying　network　efficiently.　Numerical　experiments　are　conducted　and　the　simulation　results　show　that　our　algorithm　outperform　other　algorithms　and　reduce　energy　consumption　efficiently.