| Electrical Engineering |
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| Swarm intelligence for mixed-variable design optimization |
| GUO Chuang-xin, HU Jia-sheng, YE Bin, CAO Yi-jia |
| College of Electrical Engineering, Zhejiang University, Hangzhou 310016, China |
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Abstract Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence approach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.
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Received: 09 October 2003
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