This paper presents evolutionary-based least-weight topology and size optimization procedure for designing offshore wind turbine supporting structures. A modified version of Genetic Algorithms is presented herein. The GA technique is used for solving the nonlinear constrained optimization problem of 3D quatropod jacket offshore support structure. In this optimum design formulation, the objective function is the material weight of the supporting truss; the design variables are the locations of the ends of the truss members as well as the cross-sectional areas of the truss members. The constraints are the stresses in members and the displacements of the joints. The constraints are handled using non-stationary (dynamically modified) penalty functions. The quatropod jacket, one of the most commonly used design alternatives for offshore supporting structures is presented as demonstration to the efficiency of the presented GA algorithm. The quatropod jacket test problem is subjected to gravity, wind, wave and earthquake loading conditions. The results show that the GA method is efficient in finding the best discovered optimal solution [structural topology and weight].

This paper presents evolutionary-based optimization procedure for designing natural rubber seismic isolation systems with viscous fluid dampers. The proposed technique is applied to the design of seismic isolation systems with viscous fluid dampers. A lumped-mass stick model representing a realistic five-story MDOF system with natural period of vibration ranging between 2.5 to 4.5 seconds. A suite of 24 Near-Field (NF) earthquake records representing different seismic hazard levels are utilized in the analysis and design. The damping coefficient (C), damping exponent (α) and fundamental natural period (T) are used as design variables for t he seismic isolation system. The minimization of the key response parameter, the top story acceleration ratio (TSAR) of the isolated structure compared to an identical fixed base structure, is selected as the objective function in this optimization problem. The total maximum displacements (D TM), the peak damper force (P DF), as well as the maximum drift ratio (δ max) are presented as constraints in the optimization problem. In order to achieve global optimum performance [TSAR] while handling competing constraints [D TM , P DF , δ max ], the presented GA-based technique is utilized. The commercial structural analysis software SAP2000 is utilized to perform the dynamic analysis for the MDOF system through direct Time-History Analysis (THA). The optimization algorithm is programmed in MATLAB and linked to SAP2000 through its OAPI feature. In agreement with conventional wisdom and sound engineering experience, it is found that combining low values of (C), highly nonlinear (α) [low values] with highly flexible rubber isolators [long T] produces the optimum performance.

This paper presents evolutionary-based leastweight optimization procedure for designing truss structures. A modified version of Genetic Algorithm with Domain Trimming (GADT) is developed and presented herein. The DADT is used for solving the nonlinear constrained optimization problems. In this optimum design formulation, the objective function is the material weight of the truss; the design variables are the crosssections of the truss members; the constraints are the stresses in members and the displacements of the joints. The constraints were handled using non-stationary dynamically modified penalty functions. One classical truss optimization example is presented herein to demonstrate the efficiency of the GADT algorithm. The test problem includes a 10-bar planar truss subjected to a given load condition. The result shows that the GADT method is very efficient in finding the best discovered optimal solutions, which are better of the results of other structural optimization methods.