本文考虑共享单车迁移问题, 它可看作是经典旅行售货商问题的一个新颖变形, 不同的是其目标函数为最小化碳排放。其中, 碳排放利用单车负载与其行驶路程的乘积进行刻画。我们提出了两个启发式算法：贪心和基于TSP的算法, 每个算法的核心思想均是优先减少单车负载。从理论上证明算法的可行性并给出数据实验以验证算法的实际性能。数据实验结果表明贪心算法优于基于TSP的算法, 这为共享单车企业进行日常单车分配提供了理论依据。

We formulate the sharing bicycle relocating practice as a novel optimization problem, which can be regarded as a variant of the classic TSP problem while its objective function is no longer the length of the Hamiltonian tour but the carbon emission. A well-adopted carbon emission formula that is the product of the load of the vehicle and the travel distance is employed and we propose two heuristic algorithms Greedy and TSP-based, inside both of which we set the priority to reduce the load of the vehicle for minimizing carbon emission. The feasibility of both algorithms is proven and numerical experiments are conducted to validate their performance empirically. The promise of Greedy over TSP-based algorithm is shown to the sharing bicycle companies for their daily dispatching practice.