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An efficiency‐improved genetic algorithm and its application on multimodal functions and a 2D common reflection surface stacking problem
Author(s) -
Villa Acuna Yenni Paloma,
Sun Yimin
Publication year - 2020
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12920
Subject(s) - premature convergence , genetic algorithm , computer science , convergence (economics) , stacking , mathematical optimization , algorithm , local search (optimization) , fitness function , optimization problem , reflection (computer programming) , mathematics , machine learning , physics , economics , nuclear magnetic resonance , programming language , economic growth
Although Genetic Algorithms have found many successful applications in the field of exploration geophysics, the convergence speed remains a big challenge as Genetic Algorithms usually require a huge amount of fitness function evaluations. In this paper, we propose an efficiency‐improved Genetic Algorithm, which has both a good global search capability and a good local search capability, and is also capable of robustly handling the premature convergence challenge commonly seen in linear and directed non‐linear optimization methods. In our new genetic algorithm, the global search capability is performed via a modified island model, while the local search capability is provided by a novel self‐adaptive differential evolution fine tuning scheme. Premature convergence is dealt with via a local exhaustive search method. We first demonstrate the much improved convergence speed of this efficiency‐improved Genetic Algorithm over that of our previously proposed advanced Genetic Algorithm on several multimodal functions. We further demonstrate the effectiveness of our efficiency‐improved Genetic Algorithm by applying it to a two‐dimensional common reflection surface stacking problem, which is a highly nonlinear geophysical optimization problem, to obtain very encouraging results.