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Combining Genetic Programming and Particle Swarm Optimization to Simplify Rugged Landscapes Exploration
[article]
2022
arXiv
pre-print
Most real-world optimization problems are difficult to solve with traditional statistical techniques or with metaheuristics. The main difficulty is related to the existence of a considerable number of local optima, which may result in the premature convergence of the optimization process. To address this problem, we propose a novel heuristic method for constructing a smooth surrogate model of the original function. The surrogate function is easier to optimize but maintains a fundamental
arXiv:2206.03241v1
fatcat:3tuj2pfjmrbzbo7hs7gvp6qq4e