In　the　mobile　edge　computing　(MEC)　scenarios,　users　outside　the　coverage　area　of　the　base　station　are　unable　to　offload　tasks　during　the　offloading　process.　In　this　paper,　a　resource　allocation　strategy　in　unmanned　aerial　vehicle　(UAV)-assisted　device-to-device　(D2D)　multi-relay　MEC　system　with　energy　harvesting　is　proposed.　Multiple　UAVs　are　deployed　around　the　edge　of　the　base　station　(BS)　coverage　area.　D2D　link　between　users　outside　the　BS　coverage　area　and　edge　users　of　BS　is　controlled　by　the　UAV.　Edge　users　of　BS　can　harvest　energy　from　the　UAV.　Computing　tasks　of　users　outside　the　BS　coverage　area　can　be　sent　to　edge　users　of　BS　by　different　D2D　links.　Then,　edge　users　of　BS　can　forward　computing　tasks　to　the　MEC　server　of　BS.　Transmitting　power,　energy　harvesting　time,　computing　resources,　and　channel　bandwidth　are　jointly　optimized　to　minimize　the　total　task　completion　time.　The　formulated　problem　is　a　non-convex　optimization　problem.　By　introducing　a　series　of　auxiliary　variables,　a　perspective　function　is　used　to　convert　some　non-convex　constraints　into　convex　constraints.　An　alternate　iterative　optimization　algorithm　is　adopted　to　obtain　the　optimal　solution　to　the　original　problem.　Simulation　results　show　that　compared　with　other　baseline　schemes,　the　proposed　strategy　can　reduce　the　total　task　completion　time　more　effectively.　©　2023　IEEE.