An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems |
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Authors: | S Madadgar A Afshar |
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Affiliation: | (1) Hydroinformatic Research Center, Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran;(2) Center of Excellence for Fundamental Studies in Structural Mechanics, Iran University of Science and Technology, Tehran, Iran |
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Abstract: | Ant colony optimization was initially proposed for discrete search spaces while in continuous domains, discretization of the
search space has been widely practiced. Attempts for direct extension of ant algorithms to continuous decision spaces are
rapidly growing. This paper briefly reviews the central idea and mathematical representation of a recently proposed algorithm
for continuous domains followed by further improvements in order to make the algorithm adaptive and more efficient in locating
near optimal solutions. Performance of the proposed improved algorithm has been tested on few well-known benchmark problems
as well as a real-world water resource optimization problem. The comparison of the results obtained by the present method
with those of other ant-based algorithms emphasizes the robustness of the proposed algorithm in searching the continuous space
more efficiently as locating the closest, among other ant methods, to the global optimal solution. |
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Keywords: | ACO Continuous ant algorithm Reservoir operation optimization Explorer ants Adaptation operator |
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