Inductive Program Synthesis (IPS) has been implemented by a two-stage search algorithm, Brute, and consequently improved upon with a Large Neighborhood Search (LNS) technique, in an algorithm named Vlute. Unmotivated values and design choices within Vlute caused limitations on the performance of IPS tasks. This research improves upon several of these limitations through experiments. Most significant improvements are found in the robot-planning domain through the implementation of a stochastic accept method and a best improvement neighbor search.