ON THE BENEFITS OF A DOMAIN-SPECIFIC LANGUAGE FOR MODELING METAHEURISTIC OPTIMIZATION ALGORITHMS

This work provides a case-study of how metaheuristic optimization algorithms can be developed using a domain-specific language as a separate modeling layer. A separation of the modeling process from the implementation of the algorithmic concepts improves the communication and collaboration of practitioners, optimization experts and programmers. This is achieved by providing a higher level of abstraction compared to a general-purpose programming language. A generic and extensible modeling concept is presented and several example algorithm models are illustrated.