Group Elevator Scheduling with Advanced Traffic Information for Normal Operations and Coordinated Emergency Evacuation

In a building, effective operations of transportation systems including elevators, escalators, and stairs are vital. Among them, group elevator scheduling has long been recognized as an important issue for transportation efficiency. The problem, however, is difficult because of the large state space, various traffic profiles, and uncertainties. With the progress in information technology and sensor networks, one potential way is to use advanced traffic information to reduce uncertainties and optimize the performance. How to effectively utilize such information remains an open and challenging issue. This paper presents the optimized scheduling of a group of elevators with advanced traffic information for normal operations and coordinated emergency evacuation. A look-ahead time window is first introduced to model advanced information. Key characteristics of group elevator scheduling are abstracted to establish an innovative formulation. The objective function is transformed into an additive form to facilitate the decomposition of the problem into individual car subproblems. Subproblems are independently solved by using a local search method in conjunction with dynamic programming with a novel definition of stages, states, decisions, and costs to optimize single car dispatching. With surrogate optimization, local search is “good enough” to set multiplier updating directions. Individual cars are then coordinated through the updating of multipliers by using surrogate optimization for near-optimal solutions. Numerical testing results demonstrate that near-optimal solutions are obtained for problems of moderate sizes under selected traffic patterns. The results also show the value of advanced information through testing different window sizes and rescheduling intervals.