The comparison shows that the SA algorithm could avoid the local extreme point and find the global optimal solution, the result of which has no relation to the choice of initial point. Thus a stable and reliable global optimal algorithm could be provided for the problems of ship main dimension optimization.
The path planning includes two parts, global path planning and local path planning. The Voronoi diagram of mine distribution was established, and then global optimal path was planned using genetic algorithm.
This paper gaves some research to evolutionary algorithm and the new nice mould to get the global optimization from the multi-apex function,which has the comprehensive ability to search and high precision.
To solve this problem, an improved particle swarm algorithm is proposed, which adopts the search strategy of poly-population particle to compress search space to improve the probability of searching global optimization solution.
Second, on the basis of the problem encountered during corrugated bulkhead, the optimized model is established and the global optimum solutions of the corrugated parameters, satisfying the rules requirements and the lightest corrugated bulkhead are achieved.
Since the mathematical model of pipe cablelaid vessel is very complicate and difficult to be established using traditional method,a fuzzy neural networks scheme for intelligent controlling is proposed in this paper. To simplify the calculation,a simple and practical method which is global optimum is put forward.
In order to solve the mixed design variables including continuous and discrete variables, a genetic algorithm (GA), which is able to find the global optimum solution and to greatly reduce the computational work required for choosing a proper initial solution,has been used for the optimum structural design of midship sectional transverse members of a real ship.
Experimental results have shown that a global optimal solution can be quickly obtained using the proposed method and the precision requirement for target location is satisfied.
In addition, considering the non-convex and non-concave nature of the sub-problem of combinational optimization, the branch-and-bound technique was adopted to obtain or approximate a global optimal solution.
To speed up the search process and guarantee a global optimal result, the extended compact genetic algorithm (ECGA) is used to carry out the search process.
These schemes are based on a unified theoretical base-sufficient conditions for the global optimal known in optimal control theory.
2D and 3D ASMs are combined to obtain a "global optimal" segmentation of the 3D object embedded in the data set, rather than the "locally optimal" segmentation on separate slices.