A Game-Theoretic Approach to Energy-Efficient Elevator Scheduling in Smart Buildings

Buildings, producing more carbon footprints than the transportation sector, account for a significant portion of the United States' total energy consumption. By designing modern automation techniques, smart buildings can significantly reduce energy consumption, protect the environment, and consequently improve quality of life. This article focuses on the automation of elevator scheduling, which is an NP-Hard problem, to reduce energy usage in smart buildings and improve users' quality of experience. We propose an optimal mathematical model for the elevator scheduling problem using integer programming. We then propose a novel game-theoretic approach that captures interactions within the elevator system to reduce energy consumption and enhance user experience. We propose a request coalition formation game, where nonoverlapping coalitions of user requests are served by elevators to minimize their movements and energy consumption while reducing service time and stops for users. We analyze the performance of our proposed approach using the optimal solution as a benchmark and Nearest Car and Fixed Sectoring algorithms as rivals. The experiments show that our approach is significantly efficient in terms of energy consumption and service time, making it suitable for smart buildings.

Automated summary

This article focuses on the importance of automation of elevator scheduling in reducing energy consumption and improving user experience. An optimal mathematical model and a novel game-theoretic approach are proposed to optimize energy consumption and user experience in the elevator system. Experiments show that this approach is significantly efficient in terms of energy consumption and service time, making it suitable for smart buildings.