Abstract
Elevator traffic scheduling is crucial module within an elevator group control system. An excellent scheduling approach is dedicated to both maximizing the system’s handling capacity and minimizing the passenger’s waiting time, journey time and the system’s energy consumption, especially in peak traffic pattern which usually includes up-peak, down-peak and lunch-time peak. To keep the load of elevator cars balanced in the system is one of good choices for any peak traffic. This paper proposed a novel PSO-based dynamic sectoring algorithm for elevator traffic in buildings. The service sectors corresponding to elevator cars are determined with their expected round-trip time. Our simulation results demonstrate that the proposed algorithm is an effective approach to elevator systems, which can improve the service quality of elevator system in buildings as we expect.
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Li, Z., Zhang, Y., Tan, H. (2007). Particle Swarm Optimization for Dynamic Sectoring Control During Peak Traffic Pattern. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_73
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DOI: https://doi.org/10.1007/978-3-540-74282-1_73
Publisher Name: Springer, Berlin, Heidelberg
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