Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms
Sprache des Titels:
Englisch
Original Buchtitel:
Lecture Notes in Computer Science
Original Kurzfassung:
The no free lunch (NFL) theorem puts a limit to the range
of problems a certain metaheuristic algorithm can be applied to successfully. For many methods these limits are unknown a priori and have to be
discovered by experimentation. With the use of fitness landscape analysis (FLA) it is possible to obtain characteristic data and understand
why methods perform better than others. In past research this data has
been gathered mostly by a separate set of exploration algorithms. In this
work it is studied how FLA methods can be integrated into the metaheuristic algorithm. We present a new exploratory method for obtaining
landscape features that is based on path relinking (PR) and show that
this characteristic information can be obtained faster than with traditional sampling methods. Path relinking is used in several metaheuristic
which creates the possibility of integrating these features and enhance
algorithms to output landscape analysis in addition to good solutions.
Forschungs-