ICMSEM provides a platform for researchers and practitioners of Management Science, Engineering Management and Engineering Science, to share ideas, exchange experiences. ICMSEM encourages papers that have following five elements: (1) strong background of practical management problem found in engineering practice; (2) clear problem description, and abstract it as a class of problem in Management Science and Engineering Management, topics such as decision analysis, manufacturing management, engineering project management, knowledge management, logistics, supply chain management, service innovation and management as well as a variety of multi-class interdisciplinary research; (3) effective mathematical engineering modelling, for example, creating engineering mathematical model and conducting abstract engineering mathematical analysis by using statistical mechanics, operations research, systems science, differential equations, variational inequalities, control theory, econometrics; (4) algorithm framework design, namely designing of algorithm model for solving engineering problems successfully; (5) successful application or case study in Engineering Management to show its scientificity and effectiveness.
The proceedings of the Nineteenth ICMSEM cover a wide range of areas including hot management issues in Engineering Science. It provides newest and frontier ideas and research achievements in the area of Management Science and Engineering Management to researchers and practitioners. The work contains both theoretical and practical studies of Management Science in the Computing Methodology, showing the advanced management concepts, computing technologies for decision making problems with large, uncertain and unstructured data. Research in this proceeding will show the new changes and challenges in the decision-making procedure as we have entered the big data era. Theoretical studies of this proceedings will present the new technologies of analysis, capture, search, sharing, storage, transfer, visualization, and privacy violations, as well as advances in integration of optimization, statistics and data mining. This proceeding also contains practical studies in the real decision-making scenarios when facing large, uncertain or unstructured data. The readers who are interested in related fields of can benefit from the proceedings for the new ideas and research direction.
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