Model checking problems suffer from state space explosion. State space explosion is the number of states in the graph increases exponentially with the number of variables in the state description. Searching the large graphs required in model checking requires an efficient algorithm. This dissertation explores several methods to improve an externalmemory search algorithm for model checking problems. A tool implementing these methods is built on top of the Murphi model checker. One improvement is a state cache for immediate detection leveraging the properties of state locality. A novel type of locality, intralayer locality is explained and shown to exist in a variety of search spaces. Another improvement, partial delayed duplicate detection, exploits interlayer locality to reduce search times. An automatic partitioning function is described that allows hash-based delayed duplicate detection to be used without domain knowledge of the state space. A phased delayed duplicate detection algorithm combining features of hash-based delayed duplicate detection and sorting-based delayed duplicate detection is explained and compared to the other methods.