Optimal Scheduling of Generator Maintenance Using Modified Discrete Particle Swarm Optimization
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This paper presents a modified discrete particle swarm optimization (PSO) based technique for generating optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. While GA and other analytical methods might suffer from premature convergence and the curse of dimensionality, heuristics based swarm intelligence can be an efficient alternative. PSO is known to effectively solve large scale multi-objective optimization problems. Here, a modified discrete PSO approach is proposed for the GMS optimization problem in order to overcome the limitations of the conventional methods and come up with a feasible and an optimal solution.