Computational Management Science

State of the Art 2014

Business & Finance, Management & Leadership, Operations Research, Industries & Professions, Industries
Cover of the book Computational Management Science by , Springer International Publishing
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Author: ISBN: 9783319204307
Publisher: Springer International Publishing Publication: December 22, 2015
Imprint: Springer Language: English
Author:
ISBN: 9783319204307
Publisher: Springer International Publishing
Publication: December 22, 2015
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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