Existing multiobjective evolutionary algorithms (MOEAs) perform well on multiobjective optimization problems (MOPs) with regular Pareto fronts in which the Pareto optimal solutions distribute continuously over the objective space. When the Pareto front is discontinuous or degenerated, most existing algorithms cannot achieve good results. To remedy this issue, a clustering-based adaptive MOEA (CA-MOEA) is proposed in this paper for solving MOPs with irregular Pareto fronts. The main idea is to adaptively generate a set of cluster centers for guiding selection at each generation to maintain diversity and accelerate convergence. We investigate the performance of CA-MOEA on 18 widely used benchmark problems. Our results demonstrate the competitiveness of CA-MOEA for multiobjective optimization, especially for problems with irregular Pareto fronts. In addition, CA-MOEA is shown to perform well on the optimization of the stretching parameters in the carbon fiber formation process.

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Many-objective optimization problems with degenerate Pareto fronts are hard to solve for most existing many-objective evolutionary algorithms. This is particularly true when the shape of the degenerate Pareto front is very narrow, and there are many dominated solutions near the Pareto front. To solve this particular class of many-objective optimization problems, a new evolutionary algorithm is proposed in this paper. In this algorithm, a set of reference vectors is generated to locate the potential Pareto front and then generate a set of location vectors. With the help of the location vectors, the solutions near the Pareto front are mapped to the hyperplane and clustered to generate more reference vectors pointing to Pareto front. This way, the location vectors are able to efficiently guide the population to converge towards the Pareto front. The effectiveness of the proposed algorithm is examined on two typical test problems with degenerate Pareto fronts, namely DTLZ5 and DTLZ6 with 5-40 objectives. Our experimental results show that the proposed algorithm has a clear advantage in dealing with this class of many-objective optimization problems. In addition, the proposed algorithm has also been successfully applied to optimization of process parameters of polyester fiber filament melt-transportation.

This study takes a chemical fiber factory’s spinning production line as the prototype to realize a three-dimensional virtual simulation system. Geometric three-dimensional models are constructed by exploiting the image-based three dimension reconstruction technology, in which Harris algorithm is utilized to detect corners of the modeling objects. 3DSMAX is used to give each model a highly imitative material, and deploy panoramic lighting. For virtual interaction, OGRE is utilized to realize the roaming and interaction of the virtual scene, thus finally completes a virtual simulation system for the spinning production line. Experimental results show that the system achieves a high degree of simulation of three-dimensional virtual scene and gives the user great sense of immersion, which meet the needs of virtual reality.

The management information system for compensation under multihoming network architecture has been developed in order to improve the time efficiency, accuracy, and level of informatization of compensation management in university and deal with the rising data and difficulty in exchanging information between various management information systems resulting from the changing compensation policies. This system is designed based on multihost data network architecture, including function modules of all kinds of compensation promotion, personnel historical data management, time warning, statistics, and report generation. This system integrates my five years’ experience in the front-line of compensation management work. The purpose is to fully solve the practical problems of compensation management in universities, truly help the work of compensation administrators, unify the fragmented compensation management works, and comprehensively improve the level of compensation management. It has a strong popularization and signification for reference for the compensation management work of similar universities.