Discrete genetic algorithm and real ant colony optimization for the unit commitment problem

In this paper, a cooperative metaheuristic for the solution of the Unit Commitment problem is presented. This problem is known to be a large scale, mixed integer problem. Due to combinatorial complexity, the exact solution is often intractable. Thus, a metaheuristic based method has to be used to compute a near optimal solution with low computation times. A new approach is presented here. The main idea is to couple a genetic algorithm to compute binary variables (on/off status of units), and an ant colony based algorithm to compute real variables (produced powers). Finally, results show that the cooperative method leads to the tractable computation of a satisfying solution for medium scale Unit Commitment problems.