Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
The effects of varying population density in a fine-grained parallel genetic algorithm
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An enhanced memetic differential evolution in filter design for defect detection in paper production
Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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To improve the calculation cost and the convergence to optimal solutions for multi-peak optimization problems with multiple dimensions, we propose a new evolutionary algorithm, which is an Adaptive Plan system with Genetic Algorithm (APGA). This is an approach that combines the global search ability of a GA and an Adaptive Plan with excellent local search ability. The APGA differs from GAs in how it handles design variable vectors. GAs generally encode design variable vectors into genes, and handle them through GA operations. However, the APGA encodes the control variable vectors of the Adaptive Plan, which searches for local minima, into its genes. The control variable vectors determine the global behavior of the AP, and design variable vectors are handled by the AP in the optimization process of the APGA. In this paper, the Variable Neighborhood range Control (VNC), which changes a neighborhood range based on an individual's situation--fitness, is introduced into the APGA to dramatically improve the convergence up to the optimal solution. The APGA/VNC is applied to some benchmark functions to evaluate its performance. We confirmed satisfactory performance through these various benchmark tests.