Many optimization problems in various fields have been solved using diverse optimization al gorithms. Traditional optimization techniques such as linear programming (LP), non-linear programming (NLP), and dynamic program ming (DP) have had major roles in solving these problems. However, their drawbacks generate demand for other types of algorithms, such as heuristic optimization approaches (simulated annealing, tabu search, and evolutionary algo rithms). However, there are still some possibili ties of devising new heuristic algorithms based on analogies with natural or artificial phenom ena. A new heuristic algorithm, mimicking the improvisation of music players, has been devel oped and named Harmony Search (HS). The performance of the algorithm is illustrated with a traveling salesman problem (TSP), a specific academic optimization problem, and a least-cost pipe network design problem.
The Palmer Drought Severity Index (PDSI) is used in a non‐homogeneous Markov chain model to characterize the stochastic behavior of drought. Based on this characterization an early warning system in the form of a decision tree enumerating all possible sequences of drought progression is proposed for drought management. Besides yielding probabilities of occurrence of different drought severity classes, the method associates a secondary measure in terms of likely cumulative precipitation deficit to provide timely guidance in deciding drought mitigation actions. The proposed method is particularly useful for water availability task forces in various states for issuing drought warnings in advance. The applicability of the technique is illustrated for the Tidewater climatic division of Virginia.
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