Self-Adapting Particle Swarm Optimization for continuous black box optimization

Proceedings Paper Computer Science, Artificial Intelligence

LQ-R-SHADE: R-SHADE with Quadratic Surrogate Model

Mateusz Zaborski et al.

Summary: This paper introduces an evolutionary algorithm for continuous optimization and proposes improvements. The algorithm includes components such as sample archive, meta-model, and initialization, and uses linear, quadratic, and quadratic with interactions models. Experimental results show that the proposed algorithm outperforms other methods on the COBO BBOB benchmark.

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2022, PT I (2023)

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Article Computer Science, Software Engineering

COCO: a platform for comparing continuous optimizers in a black-box setting

Nikolaus Hansen et al.

Summary: COCO is an open-source platform for Comparing Continuous Optimizers in a black-box setting, aiming to automate the benchmarking of numerical optimization algorithms. It allows benchmarking deterministic and stochastic solvers for both single and multiobjective optimization in the same framework.

OPTIMIZATION METHODS & SOFTWARE (2021)

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Article Computer Science, Artificial Intelligence

A dual opposition-based learning for differential evolution with protective mechanism for engineering optimization problems

Jiahang Li et al.

Summary: This paper proposes a novel opposition-based learning method DOBL, which tackles the classification and balance issues in OBL through two opposition strategies and a protective mechanism. Experimental results demonstrate that DOBL outperforms its competitors on the CEC2011, CEC2017, and CEC2020 test suites.

APPLIED SOFT COMPUTING (2021)

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Article Computer Science, Artificial Intelligence

Red fox optimization algorithm

Dawid Polap et al.

Summary: Foxes are popular around the globe, known for their unique hunting methods and habits. They are active throughout the year, using various tricks to hunt efficiently and adapt to changing environments. The Red Fox Optimization Algorithm (RFO) is a mathematical model developed for optimization purposes, showing potential advantages in comparison to other meta-heuristic algorithms.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Computer Science, Information Systems