Integrated order batching and picker routing (IOBPR) is a complex combinatorial optimization problem in real-world intelligent manufacturing systems. Heuristics are often used for solving such complex scheduling problems. Manually designing scheduling heuristics suffer from two limitations: 1) few problem features can be taken into account and 2) the design process is time consuming. Genetic programming hyper heuristic (GPHH) approaches have been proposed on many scheduling problems to automatically evolve effective heuristics. However, existing GPHH approaches are often problem specific and requires careful design of problem specific terminal sets and evolution operators. The aim of this work is to develop a GPHH approach to evolve heuristics for the IOBPR problem. In particular, we propose a novel terminal set (NT) with three types of terminals, and a GPHH with elitist mutation (GPHH-EM) algorithm. Extensive experiments demonstrate that the heuristics evolved by GPHH-EM can significantly outperform other state-of-the-art competing algorithms designed by human experts. Further analysis indicates that the three types of terminals effectively complement to improve evolved heuristics for decision making. Furthermore, the newly developed elitist mutation operator expedites the evolutionary process for GPHH to find high-quality heuristics.

The scientific cost drive Parameters identification and screening can improve the civil airplane development cost estimation accuracy, and then realize control and management of the development cost effectively. According to the estimation of the conceptual design stage of civil aircraft cost is studied, considering the lack of the information of civil aircraft cost parameters, parameters have been collected exist the problem of Multicollinearity, firstly, through qualitative identification method of civil aircraft cost parameter system and construct a generalized grey relative correlation model and relational clustering model combination method of screening cost drive parameters, algorithm steps are given; and collected to verify the model at home and abroad of 9 different kinds of civil aircraft information, the result shows that the proposed model can effectively screening exit key cost drive parameters. The results show that the prediction method established in this paper has improved significantly on the accuracy, illustrating the effectiveness and scientific of this method.

Cost estimation is the key problem in production management of civil aircraft. Consider the cost information of similar products can not be easily gathered, a combination model of GM (0, N) model and BP neural network algorithm is proposed. The superiorities of simulation of BP neural network algorithm and poor information generating of GM (0, N) can be effectively combined. So the new algorithm of combination model is given out. The case of cost estimation of civil aircraft is used to test the validity of the proposed model. To compare with the traditional multiple linear regression model and simple GM (0, N) model, the results indicated that the proposed model can do the work better.

Based on the present theories of buffer operators, We propose in this paper several kinds of buffer operators based on the interpolatory function, which all have the universality and practicability. we prove them to be weakening buffer operators. The problem of some contradictions between qualitative analysis and quantiative forecast in pretreatment for vibration data sequences is resolved effectively.

Based on the definition of absolute degree of grey incidence, which put forward by Professor Liu in 1992, a kind of new models for grey incidence analysis is given in this paper. The interrelations and influence can be measured by the new models with different visual angle of comparability and closeness respectively. And a simplified method to calculate the similitude degree of grey incidence and the close degree of grey incidence are put forward and proved. The properties of the new models grey incidence analysis are studied. Compared with the original definition, the new models for grey incidence analysis with many advantages and are prone to practical applications.

The authors researches the grey multi-attribute problem, in which the attribute weights and the attribute values are interval numbers, and states the decision-making method based on two-phase optimization. Firstly, a linear objective programming model is established by considering in local, and ideal attribute weight of each alternative is obtained by solving the model. Secondly, a quadratic programming model is established by considering in whole, and the solving formula of the attribute weights is given. Therefore, the complex attribute value of each alternative is obtained. Based on these values, the prioritizing or optimization for alternatives is made. Finally, a practical example is given to show the feasibility and availability of the method.

with rapid development of automobile industry in china, after-sales service market has captured both enterprises and scholars' attention, and has been a new advantage for competition. In this paper, convenience, response, waiting time, maintenance quality and etc. characterize of after-sale service in automobile industry, the new measurement model of customer satisfaction in after-sale market is proposed, and an empirical study in automobile industry is constructed. The result shows the model is simple and high-efficiency, reveals issues clearly even with poor data, and provides decision supports for after-sales management.

Grey relational analysis is an important part of the grey systems theory, and it is the basis of the grey clustering analysis, grey decision-making and grey controlling. In this paper, we provided the definitions of parallel, uniform and order-keeping properties. We constructed a new grey relational model. By theoretical proving we knew that the model is not only satisfied to the normality, whole and symmetry properties of grey relational theorems but also satisfied to the parallel, uniform, parallel order-keeping, multiple order-keeping and affine order-keeping properties.

Prediction is important for the modern scientific management. Accurate prediction can help to make correct decision and promote the decision-making quality. Grey model of prediction is a kind of forecasting model There are two unsolved problems in GM (1,1), the theoretical basis of transformation from discrete form to continuous form and the forecasting stability, which puzzled those who are absorbed in grey theory. Many scholars used different methods to revise the model, and they have made some progress, but they didn't solve it absolutely in principle. To solve these two problem and on the angle from discrete form to discrete form, discrete grey forecasting model is constructed. And the relationship between it and original grey model is studied on, also the course of instability in original grey forecasting model is found out Finally a series of accuracy index number is used to prove the unbiased property of DGM (1,1). It is indicated that the simulative result is satisfied and DGM (1,1) can be considered as the precise form of grey model and model GM (1,1) as approximate form.