Abstract
This paper describes the improved chaotic ant colony algorithm (CACA) for the preliminary ship design. An optimization model for ship design has been identified as a problem with multiple local optima representing widely varying sets of designs. The model as developed handles the ship design optimization problem as a multivariable nonlinear optimization process and aims at a global optimum solution of the problem. Ant colony algorithm (ACA) is a multi-agent optimization algorithm, which simulates the foraging behavior of ants for solving various complex combinatorial optimization problems. The CACA is based on the AC A combined with multiple scale optimization and tabu search which can improve efficiently the deficiency of long searching time and sinking into local optima of simple ACA. This algorithm was tested on some standard test functions and satisfying results were obtained. After that an attempt on solving the preliminary ship design problem, it performance was observed to be in effect.
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