Exploring Heuristic and Optimization Approaches for Elevator Group Control Systems

Abstract

This paper undertakes an examination of elevator car dispatching methods in response to hall calls. Firstly, our study focuses on the establishment of a representation of an elevator group control system as a finite-state machine to understand the dynamics of elevator group control. Secondly, two primary heuristics are explored, with the first advocating directional continuity unless the highest or lowest floor has been reached, while the second permits direction change upon completing the final call, regardless of floor extremes. Identified inefficiencies in these heuristic solutions lead us to explore enhanced alternatives. Consequently, we delve into genetic algorithm (GA) and simulated annealing (SA) methodologies. Our focus initially centers on devising solution representations and determining fitness evaluations for both approaches. We employ a simulation-based optimization approach to identify the optimal parameter values for both simulated annealing and genetic algorithms. A subsequent comparative analysis is conducted to ascertain the most effective approach among these diverse solutions. A comparative analysis reveals that the GA-based approach significantly outperforms both existing heuristics and the SA-based method in minimizing average passenger waiting time at the cost of longer computational time.