Reliability based generator maintenance scheduling using hybrid evolutionary approach

Maintenance scheduling of generating units is very important for the reliable operation of units. This paper presents a hybrid evolutionary algorithm to tackle the Generator Maintenance Scheduling (GMS) problem. The paper assumes a reliability objective function for the GMS problem. A new local search method which is derived from Extremal Optimization (EO) and Genetic Algorithm (GA) is presented. The proposed method, Hill Climbing Technique (HCT) and EO are applied to different location in GA. The selected locations are initial population, mating pool, in the offspring created by the crossover operator and in the offspring created by the mutation operator. Combination of the proposed method with HCT is also applied to the selected locations in the GA. The discussed methods are applied to a test case study and implementation and performance of the applied methods are presented. The obtained results show that the proposed method in combination with HCT yields the best results in comparison with other local search methods.