bmelacroix / mo-icop

Multi-Objective Continuous Optimisation Problems

Multi-Objective Continuous Optimisation Problems MO-ICOP

Content

• R code for generating MO-ICOP
• JMetal code for integrating generated MO-ICOPs in JMetal. In the ICOP.java file, you will need to change the path to the ICOP parameters (line 103 and 105)

PPSN2020/GECCO2021 problems

Problems used in the PPSN2020 and GECCO2021 can be found in the 'PPSN2021 problems.zip' file

The reference Pareto fronts used for calculating Hyper volumes can be found here (very large set of files) https://www.dropbox.com/sh/fpvwz8pesg42dzm/AADdOWfHmpMgOspj5ogX6y4Za?dl=0

These were correspond to all the non dominated solutions found during the experiements doen for the PPSN2021 paper.

Citation

A-C. Zăvoianu, B. Lacroix, and J. McCall. 2020. Comparative run-time performance of evolutionary algorithms on multi-objective interpolated continuous optimisation problems. In Parallel Problem Solving from Nature (PPSN XVI). Springer, 287–300.

Arnaud Liefooghe, Sébastien Verel, Benjamin Lacroix, Alexandru-Ciprian Zăvoianu, and John McCall. 2021. Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '21). Association for Computing Machinery, New York, NY, USA, 421–429. DOI:https://doi.org/10.1145/3449639.3459353