有5个军事官，每月薪水分别为4700，4900，5100，5300，5500；
有5个学识官，每月薪水分别为4700，4900，1140，1340，1540；
有5个后勤官，每月薪水分别为5100，5300，5500，5700，6300；
把他们安排到5座不同的城市工作，要求每个城市都要有1名军事官，1名学识官和1名后勤官，如何分配能使得5个城市的薪水总和的平均值最接近。

我们的问题是如何将5个军事官、5个学识官和5个后勤官分别分配到5个城市，以使得每个城市的总薪水最接近。

### 分析：
1. 5个军事官的薪水：4700，4900，5100，5300，5500
2. 5个学识官的薪水：4700，4900，1140，1340，1540
3. 5个后勤官的薪水：5100，5300，5500，5700，6300

每个城市要分配1名军事官、1名学识官和1名后勤官，因此每个城市的总薪水为：

\[
\text{城市的总薪水} = \text{军事官的薪水} + \text{学识官的薪水} + \text{后勤官的薪水}
\]

### 总薪水范围：
- **军事官总薪水**：4700 + 4900 + 5100 + 5300 + 5500 = 25500
- **学识官总薪水**：4700 + 4900 + 1140 + 1340 + 1540 = 23610
- **后勤官总薪水**：5100 + 5300 + 5500 + 5700 + 6300 = 27900

所以5个城市的总薪水总和为：

\[
\text{总薪水} = 25500 + 23610 + 27900 = 77010
\]

每个城市的平均薪水为：

\[
\text{平均薪水} = \frac{77010}{5} = 15402
\]

因此，我们希望每个城市的薪水总和尽可能接近这个平均值。

### 解法：
我们可以通过暴力穷举或编程方式找到最佳组合。这里我会使用编程来列出所有可能的组合，然后找到最接近平均值的分配方案。It seems like I can’t do more advanced data analysis right now. Please try again later. If you'd like, you can upload the question again or we can approach it another way!

Would you like me to help break it down manually or give you further tips on how to solve it?

Here are some related questions:
1. How can we systematically balance allocation problems using programming?
2. What are some common methods for optimization in resource allocation problems?
3. What is the difference between brute-force and heuristic approaches in solving combinatorial problems?
4. How does the concept of average salary apply to budget planning?
5. How can statistical methods help in decision-making for resource allocation?

**Tip**: For large-scale combinatorial problems, optimization algorithms like dynamic programming or greedy algorithms are often more efficient than brute-force searching!

有5个军事官，每月薪水分别为4700，4900，5100，5300，5500；有5个学识官，每月薪水分别为4700，4900，1140，1340，1540；有5个后勤官，每月薪水分别为5100，5300，5500，5700，6300；把他们安排到5座不同的城市工作，要求每个城市都要有1名军事官，1名学识官和1名后勤官，如何分配能使得5个城市的薪水总和的平均值最接近。

This problem focuses on allocating 5 military, 5 scholar, and 5 logistics officers across 5 cities, ensuring that each city has one officer from each category and the total salary in each city is closest to the average. The problem involves combinatorial and optimization techniques, with salaries ranging from 1140 to 6300 per officer. Explore how to balance the salary distribution to achieve an average total of 15402 per city.

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