Caching has been recognized as an effective scheme for avoiding service bottleneck and reducing network traffic in World Wide Web. Our work focuses on the replacement problem in Web caching, which arises due to limited storage. We seek the best configuration for a fully-connected network of N caches. The problem is formulated as a discrete optimization problem. A number of low-complexity heuristics are studied to obtain approximate solutions. Performances are tested under fictitious probabilistic request sequences and access logs of real Web traffic. LFD (longest-forward-distance), the classical optimal off-line paging algorithm, is observed not to be optimal. Instead a window scheme should be used. Under an unchanging request pattern, a simple static placement algorithm achieves the maximum hit rates using the arrival probabilities. Otherwise, for quick adaptation to changing requests and for better worst-case performances a randomized algorithm should be chosen. We also give an analysis of Web data to propose best heuristics for its characteristics.