Multi-Objective Particle Swarm Optimization for Decision-Making in Building Automation

Smart buildings are becoming a trend of next-generation's commercial buildings, which facilitate intelligent control of the building to fulfill occupants' needs. The primary issue of building control is that the energy consumption and the comfort value in a building environment are inevitably conflicting with each other. To study the relation between energy consumption and occupants' comfort, a multi-agent based control framework is proposed for energy and comfort management in smart building. The energy consumption and the comfort value has been considered as two control objectives and utilize Multi-Objective Particle Swarm Optimization (MOPSO) to generate the Pareto front which is formed by Pareto Optimal solutions for the multiple objective problem. The tradeoff solutions are valuable in decision-making for building energy and comfort management.