In this paper, the authors investigate the concept of adaptive path selection in optical burst-switched networks and its potential to reducing the overall burst drop probability. Specifically, the authors assume that each source maintains a (short) list of alternate paths to each destination and uses information regarding the recent congestion status of the network links to rank the paths; it then transmits bursts along the least congested path. The authors present a suite of path selection strategies, each utilizing a different type of information regarding the link congestion status, and evaluate them using simulation. The results demonstrate that, in general, adaptive path selection outperforms shortest path routing, and, depending on the path strategy involved, the network topology, and the traffic pattern, this improvement can be significant. A new framework for the development of hybrid (or meta) path selection strategies, which make routing decisions based on a weighted combination of the decisions taken by several independent path selection strategies, has been presented. This paper presents two instances of such hybrid strategies, i.e., 1) one that assigns static weights and 2) one that dynamically adjusts the weights based on feedback from the network; it has been shown that these strategies can further improve the overall burst drop probability in the network