Pareto-based Genetic Algorithm Research Articles

Multi-objective optimization of sheet metal forming process using Pareto-based genetic algorithm

Finite element analysis and optimization technique have been integrated to solve the optimal process parameters of sheet metal forming by transforming multi-objective problem into a single-objective problem in many studies. In this paper, a Pareto-based multi-objective genetic algorithm was applied to optimize sheet metal forming process. In the proposed optimal model, blank-holding force and draw-bead restraining force were optimized as design variables in order to make objective functions of fracture, wrinkle, insufficient stretching and thickness varying minimized simultaneously. The steps of optimization procedure include the using of Latin hypercube design for sample producing, response surface model for coarse fitting and incremental finite element analysis program for exact solving. An auto-body panel stamping case shows that this approach is more effective and accurate than traditional finite element analysis method and the ‘trial and error’ procedure.

A Pareto-Based Genetic Algorithm Search Approach to Handle Damped Natural Frequency Constraints in Turbo Generator Rotor System Design

The detailed design of a turbo generator rotor system is highly constrained by feasible regions for the damped natural frequencies of the system. A major problem for the designer is to find a solution that fulfills the design criterion for the damped natural frequencies. The bearings and some geometrical variables of the rotor are used as the primary design variables in order to achieve a feasible design. This paper presents an alternative approach to search for feasible designs. The design problem is formulated as an optimization problem and a genetic algorithm (GA) is used to search for feasible designs. Then, the problem is extended to include another objective (i.e., multiobjective optimization) to show the potential of using the optimization formulation and a Pareto-based GA in this rotordynamic application. The results show that the presented approach is promising as an engineering design tool.