CLPB: Chaotic Learner Performance Based Behaviour

TL;DR

This paper introduces CLPB, an improved metaheuristic algorithm enhanced with chaotic maps, which achieves faster convergence, better global optima approximation, and superior performance on large optimization problems compared to existing algorithms.

Contribution

The paper proposes Chaotic LPB (CLPB), integrating chaotic maps to significantly enhance the original LPB's performance and convergence speed in optimization tasks.

Findings

CLPB outperforms standard LPB, GA, DA, and PSO on benchmark functions.

Chaotic maps like Gauss and Tent improve CLPB's effectiveness.

CLPB handles large-scale problems more efficiently than compared algorithms.

Abstract

This paper presents an enhanced version of the Learner Performance-based Behavior (LPB), a novel metaheuristic algorithm inspired by the process of accepting high-school students into various departments at the university. The performance of the LPB is not according to the required level. This paper aims to improve the performance of a single objective LPB by embedding ten chaotic maps within LPB to propose Chaotic LPB (CLPB). The proposed algorithm helps in reducing the Processing Time (PT), getting closer to the global optima, and bypassing the local optima with the best convergence speed. Another improvement that has been made in CLPB is that the best individuals of a sub-population are forced into the interior crossover to improve the quality of solutions. CLPB is evaluated against multiple well-known test functions such as classical (TF1_TF19) and (CEC_C06 2019). Additionally, the results have been compared to the standard LPB and several well-known metaheuristic algorithms such as Dragon Fly Algorithm (DA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Finally, the numerical results show that CLPB has been improved with chaotic maps. Furthermore, it is verified that CLPB has a great ability to deal with large optimization problems compared to LPB, GA, DA, and PSO. Overall, Gauss and Tent maps both have a great impact on improving CLPB.