Preface: Special Issue on New Developments in Mathematical Programming and Operations Research

Optimization and operations research in mitigation of a pandemic (Cai-Hua Chen, Yu-Hang Du, Dong-Dong Ge, Lin Lei, Yin-Yu Ye): This paper discusses several applications of supply chain management, public resource allocation, and pandemic prevention using optimization and machine learning methods. Au...

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Vydáno v:Journal of the Operations Research Society of China (Internet) Ročník 10; číslo 2; s. 193 - 195
Hlavní autoři: Dai, Yu-Hong, Han, De-Ren, Wu, Ling-Yun, Xu, Yan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2022
Springer Nature B.V
Témata:
Algorithms
Artificial intelligence
Blockchain
Computational mathematics
Cooperation
Game theory
Machine learning
Management Science
Mathematical analysis
Mathematical programming
Mathematics
Mathematics and Statistics
Operations Research
Optimization
Pandemics
Resource allocation
Supply chains
Traveling salesman problem
Hong Kong China
China
ISSN:2194-668X, 2194-6698
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Abstract Optimization and operations research in mitigation of a pandemic (Cai-Hua Chen, Yu-Hang Du, Dong-Dong Ge, Lin Lei, Yin-Yu Ye): This paper discusses several applications of supply chain management, public resource allocation, and pandemic prevention using optimization and machine learning methods. Augmented Lagrangian methods for convex matrix optimization problems (Ying Cui, Chao Ding, Xu-Dong Li, Xin-Yuan Zhao): This paper provides a gentle introduction to the recent advances in augmented Lagrangian methods for solving large-scale convex matrix optimization problems (CMOP), and reviews two types of sufficient conditions for ensuring the quadratic growth of a class of constrained CMOP which are regularized by nonsmooth spectral functions, along with the R-superlinear convergence of the Karush–Kuhn–Tucker (KKT) residuals. Game theory and the evolution of cooperation (Bo-Yu Zhang, Shan Pei): This paper introduces related static and dynamic game methods and reviews two types of mechanisms that can promote cooperation in groups of genetically unrelated individuals, (i) direct reciprocity in repeated games and (ii) incentive mechanisms such as reward and punishment.
AbstractList Optimization and operations research in mitigation of a pandemic (Cai-Hua Chen, Yu-Hang Du, Dong-Dong Ge, Lin Lei, Yin-Yu Ye): This paper discusses several applications of supply chain management, public resource allocation, and pandemic prevention using optimization and machine learning methods. Augmented Lagrangian methods for convex matrix optimization problems (Ying Cui, Chao Ding, Xu-Dong Li, Xin-Yuan Zhao): This paper provides a gentle introduction to the recent advances in augmented Lagrangian methods for solving large-scale convex matrix optimization problems (CMOP), and reviews two types of sufficient conditions for ensuring the quadratic growth of a class of constrained CMOP which are regularized by nonsmooth spectral functions, along with the R-superlinear convergence of the Karush–Kuhn–Tucker (KKT) residuals. Game theory and the evolution of cooperation (Bo-Yu Zhang, Shan Pei): This paper introduces related static and dynamic game methods and reviews two types of mechanisms that can promote cooperation in groups of genetically unrelated individuals, (i) direct reciprocity in repeated games and (ii) incentive mechanisms such as reward and punishment.
Author Xu, Yan
Dai, Yu-Hong
Wu, Ling-Yun
Han, De-Ren
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  givenname: De-Ren
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  organization: School of Mathematical Sciences, Beihang University
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  organization: Academy of Mathematics and Systems Science, Chinese Academy of Sciences
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SubjectTerms Algorithms
Artificial intelligence
Blockchain
Computational mathematics
Cooperation
Game theory
Machine learning
Management Science
Mathematical analysis
Mathematical programming
Mathematics
Mathematics and Statistics
Operations Research
Optimization
Pandemics
Resource allocation
Supply chains
Traveling salesman problem
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