Elevator group control as a constrained multiobjective optimization problem

Modern elevator systems are controlled by the group controllers that assign moving and stopping policies to cars. Designing an adequate control (EGC) policy is challenging for a number of reasons, one them being conflicting optimization objectives. We address this task formulating corresponding constrained multiobjective problem, and, in contrast most studies domain, approach it using true methods capable finding approximations Pareto-optimal solutions. Specifically, we apply five algorithms with default constraint handling techniques demonstrate their performance optimizing EGC nine various complexity. The experimental results confirm scalability proposed methodology suggest NSGA-II equipped constrained-domination principle best performing algorithm on test systems. problem formulation allow better understanding design provide insightful information stakeholders involved deciding system configurations policies.