Elevator planning with stochastic multicriteria acceptability analysis

Modern elevator systems in high-rise buildings consist of groups of elevators with centralized control. The goal in elevator planning is to configure a suitable elevator group to be built. The elevator group must satisfy specific minimum requirements for a number of standard performance criteria. In addition, it is desirable to optimize the configuration in terms of other criteria related to the performance, economy and service level of the elevator group. Different stakeholders involved in the planning phase emphasize different criteria. Most of the criteria measurements are by nature uncertain. Some criteria can be estimated by using analytical models, while others, especially those related to the service level in different traffic patterns, require simulations. In this paper we formulate the elevator planning problem as a stochastic discrete multicriteria decision-making problem. We compare 10 feasible elevator group configurations for a 20-floor building. We evaluate the criteria related to the service level in different traffic situations using the KONE Building Traffic Simulator, and use analytical models and expert judgments for other criteria. The resulting decision problem contains mixed type criteria. Some criteria are represented by the multivariate Gaussian distribution, others by deterministic values and ordinal (ranking) information. To identify configurations that can best satisfy the goals of the stakeholders, we analyze the problem using the stochastic multicriteria acceptability analysis (SMAA) method.