A new hybrid model based on GA and PSO to the optimization of facility maintenance scheduling for organizations with assets in multiple sites

With the expansion of industries and companies, the number and dimensions of buildings and facilities of organizations are increasing, which increases the value of these assets, increasing the importance of maintenance and repairs of these facilities. On the other hand, as the number of assets increases, the process of managing their maintenance and repairs becomes more difficult than in the past. It is better to define a model for scheduling the maintenance, to proposed the optimal time and order of maintenance program. In this paper, by the combination of Genetic algorithm (GA) and Particle Swarm Optimizations (PSO), a new model for scheduling maintenance for organizations with different locations is presented. The main contributions of this paper are (a) Definition of the main problem in multiple locations and consideration of travel times between each location. (b) Consideration of different work skills for maintenance plan. (c) Consideration of the possibility of outsourcing each task. Considering 10 scenarios for the number of facilities, 3 scenarios for the number of specialists in each location and 2 scenarios for the type of costs, the results show the better performance of the proposed model in compare of three different models as Gulpiras model, Koay’s Model, and Javanmard’s model, where the results have been shown, by using the proposed model, it is possible to reduce costs just over by 34%.