Abstract: A hybrid of grid-based and graph-based search computations, together with provision of a sparse search technique effectively limited to high-probability candidate nodes provides accommodation of path constraints in an optimization search problem in substantially real-time with limited computational resources and memory. A grid of best cost (BC) values are computed from a grid of map cost (MC) values and used to evaluate nodes included in the search. Minimum segment/vector length, maximum turn angle, and maximum path length along a search path are used to limit the number of search vectors generated in the sparse search.