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1.

電子ブック
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1. Mathematical Aspects of Network Routing Optimization. 1
by Carlos A.S. Oliveira, Panos M. Pardalos
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Springer Optimization and Its Applications ; 53
オンライン: http://dx.doi.org/10.1007/978-1-4614-0311-1
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電子ブック
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2. Encyclopedia of Optimization. Second Edition
edited by Christodoulos A. Floudas, Panos M. Pardalos
出版情報: Boston, MA : Springer-Verlag, 2009
オンライン: http://dx.doi.org/10.1007/978-0-387-74759-0
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3. Sensors: Theory, Algorithms, and Applications
edited by Vladimir L. Boginski, Clayton W. Commander, Panos M. Pardalos, Yinyu Ye
出版情報: New York, NY : Springer Science+Business Media, LLC, 2012
シリーズ名: Springer Optimization and Its Applications ; 61
オンライン: http://dx.doi.org/10.1007/978-0-387-88619-0
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電子ブック
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4. Data Correcting Approaches in Combinatorial Optimization
by Boris Goldengorin, Panos M. Pardalos
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: SpringerBriefs in Optimization ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-5286-7
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5. Algorithm Portfolios : Advances, Applications, and Challenges. 1st ed. 2021
by Dimitris Souravlias, Konstantinos E. Parsopoulos, Ilias S. Kotsireas, Panos M. Pardalos
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2021
シリーズ名: SpringerBriefs in Optimization ;
オンライン: https://doi.org/10.1007/978-3-030-68514-0
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目次情報: 続きを見る
1. Metaheuristic optimization algorithms
2. Algorithm portfolios
3. Selection of constituent algorithms
4. Allocation of computation resources
5. Sequential and parallel models
6. Recent applications
7. Epilogue
References
1. Metaheuristic optimization algorithms
2. Algorithm portfolios
3. Selection of constituent algorithms
6.

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6. Introduction to Combinatorial Optimization. 1st ed. 2022
by Ding-Zhu Du, Panos M. Pardalos, Xiaodong Hu, Weili Wu
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2022
シリーズ名: Springer Optimization and Its Applications ; 196
オンライン: https://doi.org/10.1007/978-3-031-10596-8
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目次情報: 続きを見る
1. Introduction.-2. Divide-and-Conquer
3. Dynamic Programming and Shortest Path
4. Greedy Algorithm and Spanning Tree
5. Incremental Method and Maximum Network Flow
6. Linear Programming
7. Primal-Dual Methods and Minimum Cost Flow
8. NP-hard Problems and Approximation Algorithms
9. Restriction and Steiner Tree
10. Greedy Approximation and Submodular Optimization
11. Relaxation and Rounding. 12. Nonsubmodular Optimization
Bibliography
1. Introduction.-2. Divide-and-Conquer
3. Dynamic Programming and Shortest Path
4. Greedy Algorithm and Spanning Tree