Performance Analysis in Multi-KPI Optimizations

Abstract

Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.