Large Scale Optimization in Supply Chains and Smart Manufacturing
Description
In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders' decomposition, logic-based Benders' decomposition, Lagrangian relaxation, Dantzig -Wolfe decomposition, multi-tree decomposition, Van Roy' cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming.
Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management.
Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.
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Jesus Maria Velasquez Bermudez
is an entrepreneur and researcher in mathematical programming since 1976. He is the creator of OPTEX, G-SDDP, OPCHAIN, OPCHAIN-and SAAM. Bermudez received his doctorates in engineering at the Mines Faculty of the Universidad Nacional de Colombia (2006) and in industrial engineer and Magister Scientiorum at the Universidad Los Andes (Colombia, 1975). He did his postgraduate studies in planning and engineering of water resources from the Simon Bolivar University, Caracas and in Economics at Los Andes University. Bermudez has been a successful consulting engineer with experience in management of projects in mathematical modeling, industrial automation and information systems, for large companies in multiples countries. He has received several awards and has served in directorial positions of committees and societies. He was also an invited keynote speaker in the XIX Latin-Iberoamerican Conference on Operations Research (CLAIO 2018, Lima).
Marzieh Khaki?rooz has a Ph.D. in Industrial Engineering and Engineering Management and an M.S. degree in Industrial Statistics from the National Tsing Hua University (NTHU), Hsinchu, Taiwan. Currently, she is an assistant professor at school of engineering, Monterrey Institute of Technology, Mexico. Khaki?rooz has outstanding practical experience from her various global consultancies for high-tech industries. Her research interests include the application of optimization in smart manufacturing, Industry 4.0, decision making and machine teaching. She is active member of System Dynamic Society, Institute of Electrical and Electronics Engineers (IEEE), and Institute of Industrial and Systems Engineers (IISE).
Mahdi Fathi
is a Postdoctoral Associate at the Department of Industrial and Systems Engineering at Mississippi State University. He received his BS and MS from the Department of Industrial Engineering, Amirkabir University of Technology (Tehran Polytechnic) and Ph.D. from Iran University of Science and Technology, Tehran, Iran in 2006, 2008 and 2013, respectively. He is the recipient of three postdoctoral fellowships and was a visiting scholar at Center for Applied Optimization, Dept. of Industrial and Systems Engineering-University of Florida (USA) and Dept. of Electrical Engineering-National Tsing Hua University in Taiwan. He worked at Optym as a senior systems engineer and at A Model Of Reality Inc. as a system design engineer in the USA and several other companies in different industry sectors. Prof. Fathi is an active member of several societies and institutions and serves on the editorial board of several journals. His research interests include Queuing Theory and Its Applications; Stochastic Process; Optimization; Artificial Intelligent; Uncertain Quantification; Smart Manufacturing & Industry 4.0; Reliability with their applications in Health Care, Bio-medicine, Agriculture & Energy.