STACKING SEQUENCE OPTIMIZA-TION OF LAMINATED COMPOSITE CYLINDER SHELL FOR MAXIMAL BUCKLING LOAD

A new optimization method for the optimization of stacking of composite glass fiber laminates is developed. The fiber orientation and angle of the layers of the cylindrical shells are sought considering the buckling load. The proposed optimization algorithm applies both finite element analysis and the mode-pursuing sampling （MPS）method. The algorithms suggest the optimal stacking sequence for achieving the maximal buckling load. The procedure is implemented by integrating ANSYS and MATLAB. The stacking sequence designing for the symmetric angle-ply three-layered and five-layered composite cylinder shells is presented to illustrate the optimization process, respectively. Compared with the genetic algorithms, the proposed optimization method is much faster and efficient for composite staking sequence plan.

A single-level composite structure optimization method based on a blending tapered model

In order to decrease the number of design variables and improve the efficiency of com- posite structure optimal design, a single-level composite structure optimization method based on a tapered model is presented. Compared with the conventional multi-level composite structure opti- mization method, this single-level method has many advantages. First, by using a distance variable and a ply group variable, the number of design variables is decreased evidently and independent with the density of sub-regions, which makes the single-level method very suitable for large-scale composite structures. Second, it is very convenient to optimize laminate thickness and stacking sequence in the same level, which probably improves the quality of optimal result. Third, ply con-tinuity can be guaranteed between sub-regions in the single-level method, which could reduce stress concentration and manufacturing difficulty. An example of a composite wing is used to demonstrate the advantages and competence of the single-level method proposed.

An Optimization Algorithm for Service Composition Based on an Improved FOA

Large-scale service composition has become an important research topic in Service-Oriented Computing（SOC）. Quality of Service（Qo S） has been mostly applied to represent nonfunctional properties of web services and to differentiate those with the same functionality. Many studies for measuring service composition in terms of Qo S have been completed. Among current popular optimization methods for service composition, the exhaustion method has some disadvantages such as requiring a large number of calculations and poor scalability. Similarly,the traditional evolutionary computation method has defects such as exhibiting slow convergence speed and falling easily into the local optimum. In order to solve these problems, an improved optimization algorithm, WS FOA（Web Service composition based on Fruit Fly Optimization Algorithm） for service composition, was proposed, on the basis of the modeling of service composition and the FOA. Simulated experiments demonstrated that the algorithm is effective, feasible, stable, and possesses good global searching ability.