Multi-objective　vehicle　routing　problem　with　time　windows　(MOVRPTW)　is　a　canonical　logistics　problem　widely　existing　in　supply　chain.　It　is　challenging　to　obtain　the　feasible　solutions　with　fast　convergence　and　well　diversity　due　to　the　constraint　of　time　windows.　To　address　this　issue,　a　solution　evaluation-oriented　multi-objective　differential　evolution　(SE-MODE)　algorithm　is　presented　in　this　paper.　First,　a　solution　evaluation　mechanism　based　on　constraint　dominance　principle　is　developed　to　evaluate　the　dominance　degree　of　feasible　solutions　and　infeasible　solutions　quantitatively.　Second,　infeasible　solutions　with　less　dominance　degree　are　utilized　to　generate　solutions　in　the　early　stage　of　evolution　adopting　a　memetic　algorithm　framework.　Third,　a　feasible　solution-oriented　differential　mutation　strategy　is　developed　to　increase　the　probability　of　generating　feasible　solutions　and　improve　the　convergence　of　the　population.　Finally,　the　proposed　SE-MODE　algorithm　is　evaluated　on　the　RC　instances　from　Solomon,　experimental　results　show　that　SE-MODE　algorithm　is　promising　in　solving　MOVRPTW.　©　2021　IEEE.