In these cases we can still guess at roughly optimal search paths. Our final example is an operational problem, using real-world environmental data. In that case, we do not know the maximum achievable CDP , let alone the path that yields it. An operational problem Some Simple Problems Figure 1 depicts search tracks for four scenarios. Table 1 presents the evaluation results.
Evaluation results for homogeneous region.
The region is divided into 10 x 10 nm cells. In the figures, good cells are depicted in red, bad cells in blue. In order to make the detection function entirely transparent, we ignore the possible incongruity that the searcher may, in one spot, be able to detect targets 10 nm to the east, while if he were to move one inch further to the east he would only be able to detect 1 nm to the east. In the first and third examples, the searcher is constrained to start in the southwest corner. As benchmarks, we manually generated search paths that we considered near-optimal for each scenarios.