We show that the max entropy algorithm can be derandomized (with respect to a particular objective function) to give a deterministic $3/2-\epsilon$ approximation algorithm for metric TSP for some $\epsilon > 10^{-36}$. To obtain our result, we apply the method of conditional expectation to an objective function constructed in prior work which was used to certify that the expected cost of the algorithm is at most $3/2-\epsilon$ times the cost of an optimal solution to the subtour elimination LP. The proof in this work involves showing that the expected value of this objective function can be computed in polynomial time (at all stages of the algorithm's execution).

翻译：我们表明,最高通量算法可以解密(就特定目标功能而言),为公吨TSP提供3/2\ epsilon$近似值算法,用于约美元 > 10 ⁇ -36美元。为了获得我们的结果,我们将有条件期望法应用于在先前工作中构建的客观函数,用于证明该算法的预期成本最多为3/2\ epsilon美元,是冲销底盘LP的最佳解决方案成本的两倍。 这项工作的证明是表明这一目标函数的预期价值可以在多数值时间内(在算法执行的各个阶段)计算。