Complex and Intelligent Systems in Manufacturing

The scientific landscape of manufacturing systems continues to change hand in hand with the evolution of the field itself. It is anticipated that new scientific insights will impact further growth in this area. However, the number of personnel with major specialization in complex systems, those that get hired by academia and industry, remains small; yet, the professional requirements are high and include a thorough education in one or more of the following. 1)mathematics and operations research; 2)memetic computation; 3)data analytics; 4)deep learning; 5)manufacturing sciences.

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[2]  Yew-Soon Ong,et al.  Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[3]  Jie Zhang,et al.  A Simple and Fast Hypervolume Indicator-Based Multiobjective Evolutionary Algorithm , 2015, IEEE Transactions on Cybernetics.

[4]  Kay Chen Tan,et al.  A Multi-Facet Survey on Memetic Computation , 2011, IEEE Transactions on Evolutionary Computation.

[5]  Chi Xu,et al.  Sparsity adjusted information gain for feature selection in sentiment analysis , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[6]  Yew-Soon Ong,et al.  A Conceptual Modeling of Meme Complexes in Stochastic Search , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[7]  Ivor W. Tsang,et al.  Memetic Search With Interdomain Learning: A Realization Between CVRP and CARP , 2015, IEEE Transactions on Evolutionary Computation.

[8]  Ivor W. Tsang,et al.  Memes as building blocks: a case study on evolutionary optimization + transfer learning for routing problems , 2015, Memetic Comput..

[9]  Yew-Soon Ong,et al.  Multifactorial Evolution: Toward Evolutionary Multitasking , 2016, IEEE Transactions on Evolutionary Computation.

[10]  Ivor W. Tsang,et al.  The Emerging "Big Dimensionality" , 2014, IEEE Computational Intelligence Magazine.

[11]  Orkan Akcan,et al.  Big data analytics for empowering milk yield prediction in dairy supply chains , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[12]  Zhengping Li,et al.  Supplier selection decision-making in supply chain risk scenario using agent based simulation , 2015, 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).