Performance Benchmarking and Analysis of Various Elevator Dispatching Strategies

In this modern era, high-rise buildings and skyscrapers are almost everywhere and the average number of floors in a building is almost 40. Thus, elevators play a crucial role in minimizing the time taken by people to reach their desired floor. We as computer scientists need to analyze how the elevators function and thus need to study the working of elevators to improve upon the existing algorithms. The following paper is a comparative study of various elevator dispatching algorithms, their working, and the results after simulating those algorithms. It first describes the Backtracking algorithm followed by the Q-learning approach and finally the Deep Q-learning approach to tackle the optimal control problem of elevator dispatching to minimize the waiting time of the passengers. The present research was conducted to study and investigate the merits and demerits of each of these techniques and how efficiently they solve the problem at hand.