An Extensible Component-Based Multi-Objective Evolutionary Algorithm Framework

The ability to easily modify the problem definition is currently missing in Multi-Objective Evolutionary Algorithms (MOEA). Existing MOEA frameworks do not support dynamic addition and extension of the problem formulation. The existing frameworks require a re-specification of the problem definition and recompilation of source code implementing the problem specification. The presented, Controleum framework is based on Dynamic Links and a component-based system to support dynamic reconfiguration of the problem formulation without any need for recompilation of source code. Four different experiments with different compositions of objectives from the horticulture domain are formulated based on a state of the art micro-climate simulator, electricity prices and weather forecasts. The experimental results demonstrate that the Controleum framework support dynamic reconfiguration of the problem formulation without compromising the composed objectives.