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Optimization in Large Scale Problems = Industry 4.0 and Society 5.0 Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Optimization in Large Scale Problems/ edited by Mahdi Fathi, Marzieh Khakifirooz, Panos M. Pardalos.
其他題名:	Industry 4.0 and Society 5.0 Applications /
其他作者:	Fathi, Mahdi.
面頁冊數:	XI, 340 p. 87 illus., 44 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical optimization. -
電子資源:	https://doi.org/10.1007/978-3-030-28565-4
ISBN:	9783030285654

Optimization in Large Scale Problems = Industry 4.0 and Society 5.0 Applications /
Optimization in Large Scale ProblemsIndustry 4.0 and Society 5.0 Applications /[electronic resource] :edited by Mahdi Fathi, Marzieh Khakifirooz, Panos M. Pardalos. - 1st ed. 2019. - XI, 340 p. 87 illus., 44 illus. in color.online resource. - Springer Optimization and Its Applications,1521931-6828 ;. - Springer Optimization and Its Applications,104.

Part 1 -- Risk Based Optimization of Integrated Fabrication/Fulfillment Supply Chains (Nasim Nezamoddini, Faisal Aqlan, Amirhosein Gholami) -- μθ-EGF: A New Multi-Thread Implementation Algorithm for the Packing Problem inspired by Electromagnetic Fields and Gravitational Effects (Felix Martinez-Rios and Jose Antonio Marmolejo-Saucedo) -- The Vector Optimization Method for Solving Integer Linear Programming Problems. Application for the Unit Commitment Problem in Electrical Power Production (Lenar Nizamov) -- An Outer Approximation Algorithm for Capacitated Disassembly Scheduling Problem with Parts Commonality and Random Demand (Kanglin Liu, MengWang, Zhi-Hai Zhang),- Multi-Tree Decomposition Methods for Large-Scale Mixed Integer Nonlinear Optimization (Ivo Nowak, Pavlo Muts, and Eligius M.T. Hendrix) -- An Embarrassingly Parallel Method for Large-Scale Stochastic Programs (Burhaneddin Sandıkçı and Osman Y. Özaltın) -- Part 2 -- How to Effectively Train Large Scale Machines (Avan Samareh, Mahshid Salemi Parizi) -- A Graph Search Algorithm for Solving Large Scale Median Problems on Real Road Networks (Saeed Ghanbartehrania, J. David Porterb, Mahnoush Samadi Dinania) -- Solving Large Scale Optimization Problems in the Transportation Industry and Beyond through Column Generation (Yanqi Xu) -- Dynamic Energy Management (Nicholas Moehle, Enzo Busseti, Stephen Boyd, and Matt Wytock) -- An Approximation-Based Approach for Chance-Constrained Vehicle Routing and Air Traffic Control Problems (Lijian Chen) -- Algorithmic Mechanism Design for Collaboration in Large-scale Transportation Networks (Minghui Lai and Xiaoqiang Cai) -- Kantorovich-Rubinstein Distance Minimization: Application to Location Problems (Viktor Kuzmenko, Stan Uryasev).

This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.

ISBN: 9783030285654

Standard No.: 10.1007/978-3-030-28565-4doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5-402.6

Dewey Class. No.: 519.6

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