This paper proposes a genetic algorithm for solving a unit commitment schedule problem of electric generators, which formally is a mixed integer nonlinear programming problem. A chromosome represents a partial solution of binary variables. The fitness of an individual is evaluated based upon a solution of the problem where all free variables in the chromosome are relaxed to be continuous. Numerical experiments show that the proposed algorithm outperforms Lagrangian relaxation based methods developed so far.
|Journal||IEEJ Transactions on Electronics, Information and Systems|
|Publication status||Published - 2007 Jan 1|
- Genetic algorithm mixed integer nonlinear optimization
- Unit commitment problem
ASJC Scopus subject areas
- Electrical and Electronic Engineering