國立虎尾科技大學 |

Open Problems in Optimization and Data Analysis

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Open Problems in Optimization and Data Analysis/ edited by Panos M. Pardalos, Athanasios Migdalas.
其他作者:	Pardalos, Panos M.
面頁冊數:	XIX, 330 p. 43 illus., 24 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical optimization. -
電子資源:	https://doi.org/10.1007/978-3-319-99142-9
ISBN:	9783319991429

Open Problems in Optimization and Data Analysis
Open Problems in Optimization and Data Analysis[electronic resource] /edited by Panos M. Pardalos, Athanasios Migdalas. - 1st ed. 2018. - XIX, 330 p. 43 illus., 24 illus. in color.online resource. - Springer Optimization and Its Applications,1411931-6828 ;. - Springer Optimization and Its Applications,104.

Chapter 1- Social Influence-based Optimization Problems -- Chapter 2- New Statistical Robust Estimators, Open Problems -- Chapter 3- Optimal Location Problems for Electric Vehicles Charging Stations: Models and Challenges -- Chapter 4- Supply and Demand Selection Problems in Supply Chain Planning -- Chapter 5- Open problems in green supply chain modelingband optimization with carbon emission targets -- Chapter 6- Variants and Formulations of the Vehicle Routing Problem -- Chapter 7- New MIP model for Multiprocessor Scheduling Problem with Communication Delays -- Chapter 8- On Optimization Problems in Urban Transport -- Chapter 9- Some aspects of the Stackelberg Leader/Follower Model -- Chapter 10- Open research areas in distance geometry -- Chapter 11- A Circle Packing Problem and its Connection to Malfatti’s Problem -- Chapter 12- Review of basic local searches for solving the Minimum sum-of-squares clustering problem -- Chapter 13- On the Design of Metaheuristics-based Algorithm Portfolios -- Chapter 14- Integral Simplex Methods for the Set Partitioning Problem: Globalization and Anti-Cycling -- Chapter 15- Open problems on Benders Decomposition Algorithm -- Chapter 16- An Example of Nondecomposition in Data Fitting by Piecewise Monotonic Divided Differences of Order Higher than Two.

Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016. .

ISBN: 9783319991429

Standard No.: 10.1007/978-3-319-99142-9doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5-402.6

Dewey Class. No.: 519.6

Open Problems in Optimization and Data Analysis
LDR:03769nam a22003975i 4500 001 989662
003 DE-He213
005 20200704103855.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319991429 $9 978-3-319-99142-9
024 7 $a 10.1007/978-3-319-99142-9 $2 doi
035 $a 978-3-319-99142-9
050 4 $a QA402.5-402.6
072 7 $a PBU $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBU $2 thema
082 0 4 $a 519.6 $2 23
245 1 0 $a Open Problems in Optimization and Data Analysis $h [electronic resource] / $c edited by Panos M. Pardalos, Athanasios Migdalas.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XIX, 330 p. 43 illus., 24 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Optimization and Its Applications, $x 1931-6828 ; $v 141
505 0 $a Chapter 1- Social Influence-based Optimization Problems -- Chapter 2- New Statistical Robust Estimators, Open Problems -- Chapter 3- Optimal Location Problems for Electric Vehicles Charging Stations: Models and Challenges -- Chapter 4- Supply and Demand Selection Problems in Supply Chain Planning -- Chapter 5- Open problems in green supply chain modelingband optimization with carbon emission targets -- Chapter 6- Variants and Formulations of the Vehicle Routing Problem -- Chapter 7- New MIP model for Multiprocessor Scheduling Problem with Communication Delays -- Chapter 8- On Optimization Problems in Urban Transport -- Chapter 9- Some aspects of the Stackelberg Leader/Follower Model -- Chapter 10- Open research areas in distance geometry -- Chapter 11- A Circle Packing Problem and its Connection to Malfatti’s Problem -- Chapter 12- Review of basic local searches for solving the Minimum sum-of-squares clustering problem -- Chapter 13- On the Design of Metaheuristics-based Algorithm Portfolios -- Chapter 14- Integral Simplex Methods for the Set Partitioning Problem: Globalization and Anti-Cycling -- Chapter 15- Open problems on Benders Decomposition Algorithm -- Chapter 16- An Example of Nondecomposition in Data Fitting by Piecewise Monotonic Divided Differences of Order Higher than Two.
520 $a Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016. .
650 0 $a Mathematical optimization. $3 527675
650 0 $a Production management. $3 566447
650 0 $a Software engineering. $3 562952
650 0 $a Computer mathematics. $3 1199796
650 1 4 $a Optimization. $3 669174
650 2 4 $a Operations Management. $3 1069063
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 669780
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 669338
700 1 $a Pardalos, Panos M. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 669384
700 1 $a Migdalas, Athanasios. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1067394
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319991412
776 0 8 $i Printed edition: $z 9783319991436
830 0 $a Springer Optimization and Its Applications, $x 1931-6828 ; $v 104 $3 1255232
856 4 0 $u https://doi.org/10.1007/978-3-319-99142-9
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)