International Journal of Bio-Inspired Computation · 2009 · 470 citations · 11 references
ComputingWater Resources ManagementAlgorithmsOptimizationPath PlanningCombinatorial OptimizationEvolutionary ComputationEvolutionary OptimizationHeuristic OptimizationHeuristic SearchMetaheuristic OptimizationAnt Colony OptimizationEvolutionary AlgorithmsHeuristic AlgorithmsHeuristic ComputationKnapsack ProblemsN-queens ProblemParticle Swarm OptimizationTraveling Salesman Problem
A natural river often finds good paths among lots of possible paths in its ways from the source to destination. These near optimal or optimal paths are obtained by the actions and reactions that occur among the water drops and the water drops with the riverbeds. The intelligent water drops (IWD) algorithm is a new swarm-based optimisation algorithm inspired from observing natural water drops that flow in rivers. In this paper, the IWD algorithm is tested to find solutions of the n-queen puzzle with a simple local heuristic. The travelling salesman problem (TSP) is also solved with a modified IWD algorithm. Moreover, the IWD algorithm is tested with some more multiple knapsack problems (MKP) in which near-optimal or optimal solutions are obtained.
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