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- W2096295989 abstract "This paper presents a new cooperative coevolutionary algorithm (CCA) for power system unit commitment. CCA is an extension of the traditional genetic algorithm (GA) which appears to have considerable potential for formulating and solving more complex problems by explicitly modeling the coevolution of cooperating species. This method combines the basic ideas of Lagrangian relaxation technique (LR) and GA to form a two-level approach. The first level uses a subgradient-based stochastic optimization method to optimize Lagrangian multipliers. The second level uses GA to solve the individual unit commitment sub-problems. CCA can manage more complicated time-dependent constraints than conventional LR. Simulation results show that CCA has a good convergent property and a significant speedup over traditional GAs and can obtain high quality solutions. The curse of dimensionality is surmounted, and the computational burden is almost linear with the problem scale." @default.
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- W2096295989 date "2002-01-01" @default.
- W2096295989 modified "2023-09-27" @default.
- W2096295989 title "Cooperative Coevolutionary Algorithm for Unit Commitment" @default.
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- W2096295989 doi "https://doi.org/10.1109/mper.2002.4311691" @default.
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