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A hybrid method of evolutionary algorithms for mixed-integer nonlinear optimization problems

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3 Author(s)
Yung-Chien Lin ; Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi, Taiwan ; Feng-Sheng Wang ; Kao-Shing Hwang

A hybrid method of evolutionary algorithms, called mixed-integer hybrid differential evolution (MIHDE), is proposed in this study. In the hybrid method, a mixed coding is used to represent the continuous and discrete variables. A rounding operation in the mutation is introduced to handle the integer variables so that the method is not only used to solve mixed-integer nonlinear optimization problems, but also used to solve the real or integer nonlinear optimization problems. The accelerated phase and migrating phase are implemented in MIHDE. These two phases acted as a balancing operator are used to explore the search space and to exploit the best solution. Both examples of mechanical design are tested by the MIHDE. The computation results demonstrate that the MIHDE is superior to other methods in terms of solution quality and robustness property

Published in:

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on  (Volume:3 )

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