Abstract: This repository provides extensive detail on the newly generated Generalized Numerical Benchmark Generator for 2025 CEC & GECCO Competitions (GNBG-II), consisting of 24 well-defined box-constrained problem instances.

Dec 12, 2023 · This paper introduces the Generalized Numerical Benchmark Generator (GNBG) for single-objective, box-constrained, continuous numerical optimization. Unlike existing approaches that rely on multiple baseline functions and transformations, GNBG utilizes a single, parametric, and configurable baseline function.

MATLAB source code of the generalized numerical benchmark generator (GNBG). This code includes the GNBG problem instance generator. - Danial-Yazdani/GNBG_Generator.MATLAB

Dec 12, 2023 · This document introduces a set of 24 box-constrained numerical global optimization problem instances, systematically constructed using the Generalized Numerical Benchmark Generator (GNBG).

This competition invites prospective researchers to evaluate the performance of their algorithms on a newly designed set of 24 problem instances generated using the Generalized Numerical Benchmark Generator (GNBG).

This paper introduces the Generalized Numerical Benchmark Generator (GNBG) for single-objective, box-constrained, continuous numerical optimization. Unlike existing approaches that rely on multiple baseline functions and

This paper introduces the Generalized Numerical Benchmark Generator (GNBG) for single-objective, box-constrained, continuous numerical optimization. Unlike existing approaches that rely on multiple baseline functions and transformations, GNBG utilizes a single, parametric, and configurable baseline function.

This paper introduces the Generalized Numerical Benchmark Generator (GNBG) for single-objective, box-constrained, continuous numerical optimization. Unlike existing approaches that rely on multiple baseline functions and transformations, GNBG utilizes a single, parametric, and configurable baseline function.

Researchers using GNBG can generate instances that cover a broad array of morphological features, from unimodal to highly multimodal functions, various local optima patterns, and symmetric to highly asymmetric structures.

MATLAB source code of the generalized numerical benchmark generator (GNBG). This version includes a number of predefined GNBG-generated problem instances. - Danial-Yazdani/GNBG_Instances.MATLAB