Application Of Bionic Optimization Algorithms To The Spot Color Matching And Ink Preset In Offset Printing

The artificial intelligent technology is addressed a remarkable advance in recent years, especially, the bionic optimization algorithms. The proposing of these algorithms are mostly inspired by biological group behaviors in the nature, the development of the optimization algorithms provide an effective alternative for solving complex optimization problem. In this dissertation, two typical and widely used bionic optimization algorithms, namely, harmony search optimization algorithm and biogeography based optimization algorithm, are discussed. Based on the analysis of each algorithm, some local searching strategies are employed to improve its performance, and further applied to deal with some practical problems in offset printing. In general, the main works and contributions of this dissertation can be summarized as follows:(1) The framework of bionic optimization algorithm model is summarized, and some improvement strategies and mechanisms are presented. Furthermore, the biogeography-based optimization (BBO) is employed as an example, and a BBO based hybrid algorithm is proposed. In this hybrid algorithm, the opposition based learning (OBL) approach is utilized to generate a better initial population, and the pitch adjusting mechanism in HS is employed to enhance the local searching ability. By fusing the operators in BBO with the OBL and pitch adjusting mechanisms, the exploration and exploitation capability may be enhanced and well balanced, and thus result in a more effective algorithm for global optimization. The proposed hybrid algorithm is further applied to the parameter estimation of chaotic systems to verify its performance. Numerical simulations are conducted on some typical chaotic systems with or without time-delay, the results show that, whatever the noise is concerned or not, the proposed scheme can obtain better estimated results than some typical existing algorithms, and the effectiveness and robustness of the proposed scheme are also demonstrated by the results.(2) The problem in the spot color matching (SCM) algorithm is studied and analyzed, and a spectrophotometric based SCM model is proposed, and can be converted into a multiple constraints complex optimization problem for its feature. The aforementioned BBO based hybrid algorithm is further improved by employing a constraint handling method, and applied to solve this problem. The experiments are conducted on some randomly selected testing samples, and the comparisons between the proposed algorithm and some other typical methods show that, for all of the samples, the proposed algorithm exhibits better convergence performance. Further comparisons are conducted between the proposed SCM model and the widely used spot color matching FM III software, the experimental results show that, in most cases, the proposed model can achieve more accuracy color matching results than the FM III software in terms of color difference, and all of the color differences obtained by the proposed model, in fact, are lower to the acceptability limit.(3) On the analysis of the offset printing technique and the corresponding ink system, a global harmony search optimization (GHSO) based ink preset method is proposed, and the nonlinear relationship model between the dot area rate and the corresponding ink key opening degree in each ink area is also established by the least squared support vector machine. The GHSO is used to optimize the parameters in the model, which is further applied to solve the ink preset problem of offset printing. The experimental results show that, the proposed GHSO has the features of easy complementation, fast running and strong optimization ability. The results of comparison with real printing data proved the validity of the proposed scheme, and the GHSO based ink preset model also has higher precision than the preset device of Roland printing machine.