我说这些是为了参加编程比赛。一般来说，他们有非常大的输入，除以2会发生很多次，已知输入是正的或负的。

X >>1比X /2好。我在ideone.com上运行了一个程序，其中发生了超过10^10除以2的运算。X /2花了将近5.5s，而X >>1花了将近2.6s。

只是加了一个注释

在一些基于vm的语言中，x *= 0.5通常会更快——尤其是actionscript，因为变量不需要被检查是否除以0。

使用最能描述您要做的事情的操作。

如果你将数字作为一个比特序列来处理，请使用bitshift。 如果你把它当作一个数值，使用除法。

请注意，它们并不完全相等。对于负整数，它们可以给出不同的结果。例如:

-5 / 2  = -2
-5 >> 1 = -3

(ideone)

我们有很多理由支持使用x = x / 2;以下是一些例子:

it expresses your intent more clearly (assuming you're not dealing with bit twiddling register bits or something) the compiler will reduce this to a shift operation anyway even if the compiler didn't reduce it and chose a slower operation than the shift, the likelihood that this ends up affecting your program's performance in a measurable way is itself vanishingly small (and if it does affect it measurably, then you have an actual reason to use a shift) if the division is going to be part of a larger expression, you're more likely to get the precedence right if you use the division operator: x = x / 2 + 5; x = x >> 1 + 5; // not the same as above signed arithmetic might complicate things even more than the precedence problem mentioned above to reiterate - the compiler will already do this for you anyway. In fact, it'll convert division by a constant to a series of shifts, adds, and multiplies for all sorts of numbers, not just powers of two. See this question for links to even more information about this.

简而言之，当你真正想要进行乘法或除法运算时，编写移位代码并没有什么好处，除了可能会增加引入错误的可能性。自从编译器不够聪明到在适当的时候优化这类事情到移位以来，已经过去了。

X/Y是正确的…和" >> "移位运算符..如果我们想要二除一个整数，我们可以使用(/)被除数运算符。移位运算符用于移位位。

x = x / 2; x / = 2;我们可以这样用…

x / 2更清晰，x >> 1快不了多少(根据一个微基准测试，对于Java JVM快30%左右)。正如其他人所注意到的，对于负数，舍入略有不同，所以当您想处理负数时必须考虑这一点。一些编译器可能会自动将x / 2转换为x >> 1，如果他们知道这个数字不可能是负数(即使我无法验证这一点)。

即使x / 2可能不使用(慢)除法CPU指令，因为一些捷径是可能的，但它仍然比x >> 1慢。

(This is a C / C++ question, other programming languages have more operators. For Java there is also the unsigned right shift, x >>> 1, which is again different. It allows to correctly calculate the mean (average) value of two values, so that (a + b) >>> 1 will return the mean value even for very large values of a and b. This is required for example for binary search if the array indices can get very large. There was a bug in many versions of binary search, because they used (a + b) / 2 to calculate the average. This doesn't work correctly. The correct solution is to use (a + b) >>> 1 instead.)