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In the information technology age, informationization is the inevitable development trend of the industries pertaining to medical, social, manufacturing, or engineering fields. From the individual information query to the allocation of thousands of resources and staff, all the information operations involved is a part of the process of informationization. In the past few decades, the computing hardware and software has continued to grow exponentially. Furthermore, breakthrough in operational research and arrival of the era of big data has helped us to find a better solution for human information needs. However, there still are some challenging problems for providing a better service. For most given problems, multi-objective optimization and data mining can provide the optimal solution. And machine learning such as artificial neural network, deep learning, evolutionary algorithm, and genetic algorithm are some of the other well-established techniques we can explore for solutions generation. In the typical industry, using these algorithms can help organizations find the potential factors which affect their customers more accurately and improve service provision. It can also identify trends that bridge the gaps among fragments of seemingly unrelated information. In addition, the process of informationtization also promotes the development of informatics, including membrane computing, gene expressions, genetic computing, etc. These new technologies can offer much higher quality and personalized service for people. Multi-objective optimization and data analysis techniques that are related to informationization have been applied in major fields of engineering and management pertaining to resource allocation and planning. In particular, informationization has appeared in industries such as agriculture, education, etc. Furthermore, computer vision and imaging is used for data analysis and health diagnostics in the medical industry, and also for structural analysis in the manufacturing industry. In this edito-

Multi-objective optimization and data analysis in informationization