Creative Conception Design Based On Intelligent Optimization Technology

With the saturation of commodities and the acceleration of consuming speed, the consumers'demands tend to be more and more various and characteristic, and the purchasing behavior is more selective. Facing this reality, many enterprises begin to realize the importance of product design and pay more attention to creative products. Creative design can satisfy the novel and ever-changing market demands and help to make products more competitive. Thus, innovative design has become one of the popular research items in computer-aided design field in recent years.The rise of intelligent optimization technology provides us a new approach for exploring conceptually creative design that is evolving. Evolutionary design is a type of design process for improvement to meet the demands of new products while preserve the excellent performance of existing products. Evolutionary design applies a variety of intelligent optimization technology to different design fields. The required design results are obtained through intelligent optimization algorithm (genetic algorithm, particle swarm optimization, differential evolution, etc.) that is the basic computational tool and a combined computation of various design theory. As the evolutionary design approach can mimic genetic characteristics such as the biological crossover and mutation of chromosome, the advantage of evolutionary design consists in obtaining humanlike intelligence, as well as quick and effective solutions of general problems.In fact, the evolutionary design methodology has become one of the most important innovative design techniques; moreover, Intelligent Optimization technology has begun to be applied to innovative conceptual design. This thesis reviewed the intelligent optimization algorithms, including its origin, fundamental principles, mechanisms, features, as well as applications. In addition to this, the thesis improved the particle swarm algorithm and applied it to the innovative conceptual design in optical area, furthermore, CATIA secondary development technology was used to realize innovative design.The main innovation of this paper is as follows:1. Designed to improve particle swarm optimization, accede to dynamic linear inertia weight adjustment programs, and proposed a local search strategy based on improved PSO algorithm. The basic particle swarm algorithm is improved through the location optimization of particles, so that the particle position can be guided in the optimization process, the local search capability of the particle in the vicinity of the optimum point is enhanced, and the convergence rate is greatly speeded up. Additionally, four test functions were experimentalized to verify and improve the validity and superiority.2. The particle swarm algorithm based on local search strategy is applied to innovative conceptual design in optical area. Experiments show that optical innovative conceptual design based on PSO can generate innovative products that meet customer needs more quickly, almost without the intervention of designers. This can help with the designers to free from heavy manual work, so as to open up new intelligent optimization applications, as well as provide a new method for glasses innovative design.