IEEE Access · 2021 · 10 citations · 28 references
EngineeringIndustrial EngineeringMaintenance EngineeringOptimizationSchedulingMaintenance OptimizationMaintenance SchedulingMulti-objective SchedulingPreventive MaintenanceScheduling OptimizationScheduling TheoryElectrical Power SystemsExchange AlgorithmMetaheuristic SchedulingMetaheuristic SearchMulti-objective Maintenance SchedulingMulti-objective Preventive Maintenance SchedulingMulti-objective Scheduling MetaheuristicsPreventive Maintenance Scheduling
The complexity of power systems is increasing as new generating units are added to power systems in order to supply power to the growing economies. This has resulted in further research into the generator maintenance scheduling (GMS) problem which seeks to ensure optimal preventive maintenance scheduling that is effective and reliable. This research is focused on developing a generator maintenance schedule using a tri-objective model. The GMS tri-objective model is solved using two solution methodologies. The first is an exact solution method using mathematical modelling software, Advanced Interactive Multidimensional Modelling System (AIMMS). The second solution method is a recently developed metaheuristic algorithm called Exchange Market Algorithm (EMA). Results show that the tri-objective model finds a trade-off solution of the individual solution methods. The metaheuristic algorithm gives a better solution for larger optimization problems.
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Firefly Algorithm: Recent Advances and Applications
2013 · 709 citations
Naser Ghorbani, Ebrahim Babaei · Applied Soft Computing · 2014 · 269 citations