Benchmark tests of evolutionary algorithms: mathematic evaluation and application to water distribution systems

Benchmark tests of evolutionary algorithms: mathematic evaluation and application to water distribution systems

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Article ID: iaor20062829
Country: Canada
Volume: 7
Issue: 1
Start Page Number: 26
End Page Number: 37
Publication Date: Mar 2006
Journal: Journal of Environmental Informatics
Authors: , ,
Keywords: heuristics, geography & environment
Abstract:

Evolutionary Algorithms (EAs) are a set of probabilistic optimization algorithms based on an analogy between natural biological systems and engineered systems. In this paper, the computational performance of a set of specific EAs (specifically, the Genetic Algorithm, Evolutionary Programming, Particle Swarm Optimization, Ant Colony Optimization and Shuffled Complex Evolution Algorithm) is compared using a set of four mathematical test objective functions. In addition, a hybridization of EAs with other local search methods is introduced to improve or fine-tune the performance of the primary EA. As a case study, the EAs are applied to a calibration problem for a water distribution system and ably show their robust and global convergence characteristics.

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