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Computational management science: state of the art 2014

Contributor(s): Material type: TextTextSeries: Lecture Notes in Economics and Mathematical Systems; (Vol 682)Publication details: Springer 2016 LondonDescription: xxi, 245 pISBN:
  • 9783319204291
Subject(s): DDC classification:
  • 658 C6
Summary: This volume contains contributions from the 11th International Conference on Management Science (CMS 2014), held at Lisbon, Portugal, on May 29-31, 2014. Its contents reflect the wide scope of Management Science, covering different theoretical aspects for a quite diverse set of applications. Computational Management Science provides a unique perspective in relevant decision-making processes by focusing on all its computational aspects. These include computational economics, finance and statistics; energy; scheduling; supply chains; design, analysis and applications of optimization algorithms; deterministic, dynamic, stochastic, robust and combinatorial optimization models; solution algorithms, learning and forecasting such as neural networks and genetic algorithms; models and tools of knowledge acquisition, such as data mining; and all other topics in management science with the emphasis on computational paradigms. http://www.springer.com/gp/book/9783319204291
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Holdings
Item type Current library Item location Collection Shelving location Call number Status Date due Barcode
Books Vikram Sarabhai Library Rack 35-A / Slot 1843 (2nd Floor, East Wing) Non-fiction General Stacks 658 C6 (Browse shelf(Opens below)) Available 194134

Table of Contents:

Part I: Energy
Part II: Logistics
Part III: Production
Part IV: Optimization Methods

This volume contains contributions from the 11th International Conference on Management Science (CMS 2014), held at Lisbon, Portugal, on May 29-31, 2014. Its contents reflect the wide scope of Management Science, covering different theoretical aspects for a quite diverse set of applications. Computational Management Science provides a unique perspective in relevant decision-making processes by focusing on all its computational aspects. These include computational economics, finance and statistics; energy; scheduling; supply chains; design, analysis and applications of optimization algorithms; deterministic, dynamic, stochastic, robust and combinatorial optimization models; solution algorithms, learning and forecasting such as neural networks and genetic algorithms; models and tools of knowledge acquisition, such as data mining; and all other topics in management science with the emphasis on computational paradigms.

http://www.springer.com/gp/book/9783319204291

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