Elevator group optimization in a smart building

Solving elevator group scheduling problem via the use of meta-heuristic optimization techniques is studied in this research. Majority of the current research has considered the service time as the measurement of elevator performance while the engineering culture is gradually trending towards the greener technology that weighs the lower energy consumption of elevator systems as a desirable feature for building designs. From service time optimization techniques of the existing body of research a technique based on a trip scheduling model and the branch and bound algorithm is independently replicated to study its capacity to produce competitive results. Then the optimization criterion is modified by adding an energy consumption measure of the elevator group. Several result sets over different dimensions of the problem space were recorded to evaluate this approach. It is shown that newly proposed technique can achieve better energy consumption measures in a range of configurations of the problem space with better or approximately equal service time performance. The overall energy consumption reduction is 20% in the generic scenario while the service time advantage is 13%. The stability of the algorithm is also shown for mid and high rise buildings.