Conference Proceeding

Synthetic vs. Real-World Continuous Landscapes: A Local Optima Networks View


Contreras-Cruz MA, Ochoa G & Ramirez-Paredes JP (2020) Synthetic vs. Real-World Continuous Landscapes: A Local Optima Networks View. In: Filipič B, Minisci E & Vasile M (eds.) Bioinspired Optimization Methods and Their Applications. Lecture Notes in Computer Science, 12438. 9th International Conference, BIOMA 2020, Brussels, Belgium, 19.11.2020-20.11.2020. Cham, Switzerland: Springer International Publishing, pp. 3-16.

Local optima networks (LONs) are a useful tool to analyse and visualise the global structure of fitness landscapes. The main goal of our study is to use LONs to contrast the global structure of synthetic benchmark functions against those of real-world continuous optimisation problems of similar dimensions. We selected two real-world problems, namely, an engineering design problem and a machine learning problem. Our results indicate striking differences in the global structure of synthetic vs real-world problems. The real-world problems studied were easier to solve than the synthetic ones, and our analysis reveals why; they have easier to traverse global structures with fewer nodes and edges, no sub-optimal funnels, higher neutrality and multiple global optima with shorter trajectories towards them.

Local optima networks Funnel structures; Fitness landscapes; Real-world optimisation problems

Title of seriesLecture Notes in Computer Science
Number in series12438
Publication date31/12/2020
Publication date online16/11/2020
PublisherSpringer International Publishing
Place of publicationCham, Switzerland
ISSN of series0302-9743
Conference9th International Conference, BIOMA 2020
Conference locationBrussels, Belgium

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