The search theory open literature has paid little, if any, attention to the multiple-searcher, moving-target search problem. We develop an optimal branch-and-bound procedure and six heuristics for solving constrained-path problems with multiple searchers. Our optimal procedure outperforms existing approaches when used with only a single searcher. For more than one searcher, the time needed to guarantee an optimal solution is prohibitive. Our heuristics represent a wide variety of approaches: One solves partial problems optimally, two use paths based on maximizing the expected number of detections, two are genetic algorithm implementations, and one is local search with random restarts. A heuristic based on the expected number of detections obtains solutions within 2% of the best known for each one-, two-, and three-searcher test problem considered. For one-and two-searcher problems, the same heuristic's solution time is less than that of other heuristics. For threesearcher problems, a genetic algorithm implementation obtains the best-known solution in as little as 20% ofother heuristic solution times. 0 1996 John Wiley & Sons, Inc. The constrained-path, moving-target search problem [ 6 , 15, 161 has the following characteristics: 0 A single searcher and target move among a finite set of cells in discrete time. 0 The searcher and target occupy only one cell each time period. 0 Each time period, the searcher moves from its current cell to one of a specified 0 The target moves among cells according to a specified stochastic process. 0 If the target occupies the searched cell, the random search formula determines the probability of detection-otherwise the detection probability is zero. 0 The target's probability distribution is Bayesian updated for nondetection each time period. set of accessible cells.The objective of the search is to find a feasible search path that maximizes the probability of detecting the target in T time periods. The main contributions of this article center around extending the constrained-path, moving-target search problem to consider multiple searchers explicitly. As this article demonstrates, exact procedures developed to effectively solve single-searcher versions of this
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