Implementation of the scalable multi-objective test problems proposed in:
S. Zapotecas-Martínez, C.A. Coello Coello, H.E. Aguirre & K. Tanaka (2023). Challenging test problems for multi-and many-objective optimization. Swarm and Evolutionary Computation, Volume 81, 101350, ISSN 2210-6502. https://doi.org/10.1016/j.swevo.2023.101350
This source code presents the implementation of the ZCAT multi-objective test problems according to the description given in the paper: "Challenging test problems for multi- and many-objective optimization".
The "main.c" file contains three examples of the use of this implementation.
Example 1 shows how to generate (in the allowed decision space) and evaluate a single random solution to the ZCAT1 problem.
Example 2 shows how to generate random optimal solutions and use the ZCAT functions to evaluate any solution defined in the allowed decision space.
Example 3 automatically generates a given number of optimal solutions for all ZCAT problems.
NOTE: In this implementation, the generation of Pareto optimal solutions (for problems with disconnected Pareto fronts) is limited to 15 objectives. Contact me if you need Pareto optimal solutions for more than 15 objectives in these types of problems.