Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
| Hi-index | 0.00 |
This paper presents a new constraint-handling genetic approach for solving the economic dispatch problem in electric power systems. A real code genetic algorithm is implemented to minimize the active power generation cost while satisfying power balance (energy conservation) and generation limit constraints simultaneously during the optimization process. This is achieved by introducing a novel strategy for searching the solution on the energy conservative space, producing only individuals that fulfill the energy conservation constraint, and reducing the search space in one dimension. Computer simulations on three benchmark electrical systems show the prowess of the proposed approach whose results are very close to those reported by other authors using different methods.