Order　scheduling　is　an　important　part　of　the　e-waste　recycling　process,　which　can　influence　the　quantity　and　efficiency　of　the　recycling.　With　the　sustainable　development　of　e-waste　recycling,　low-carbon　order　scheduling　becomes　a　significant　and　challenging　reverse　logistics　scheduling　problem.　However,　it　is　difficult　to　obtain　an　effective　low-carbon　order　schedule　considering　the　conflicting　interests　of　the　multiple　stakeholders,　including　enterprises,　drivers,　customers,　and　governments.　To　address　this　issue,　a　multiobjective　order　scheduling　model　(MOOSM)　and　a　multiobjective　differential　evolution　algorithm　balancing　multiple　stakeholders　(MODE-MS)　are　proposed　in　this　article.　First,　to　embody　the　interests　of　different　stakeholders,　three　time-dependent　key　variables　are　calculated　by　the　road　congestion　and　vehicle　load,　including　the　velocity,　traveling　time,　and　carbon　emission.　Second,　with　the　above　key　variables,　a　five-objective　order　scheduling　model　is　formulated　to　describe　the　low-carbon　order　scheduling　problem　in　e-waste　recycling.　Third,　for　solving　the　MOOSM,　a　multiobjective　differential　evolution　algorithm　based　on　an　adaptive　evolutionary　search　strategy　is　developed　to　obtain　the　low-carbon　and　stakeholders　satisfied　scheduling　schemes.　The　experimental　results　validate　the　feasibility　of　MOOSM　and　the　effectiveness　of　MODE-MS.　By　comparing　with　four　state-of-the-art　algorithms,　the　advantages　of　the　proposed　MODE-MS　are　further　demonstrated　in　solving　the　low-carbon　order　scheduling.