MARC Record from harvard_bibliographic_metadata

LEADER: 03422nam a22004695a 4500
001 013607877-X
005 20130308190537.0
008 130131s2013 xxu| s ||0| 0|eng d
020 $a9781461462774
020 $a9781461462774
020 $a9781461462767
024 7 $a10.1007/978-1-4614-6277-4$2doi
035 $a(Springer)9781461462774
040 $aSpringer
050 4 $aQA402-402.37
050 4 $aT57.6-57.97
072 7 $aKJT$2bicssc
072 7 $aKJM$2bicssc
072 7 $aBUS049000$2bisacsh
072 7 $aBUS042000$2bisacsh
082 04 $a519.6$223
100 1 $aNagurney, Anna.
245 10 $aNetworks Against Time :$bSupply Chain Analytics for Perishable Products /$cby Anna Nagurney, Min Yu, Amir H. Masoumi, Ladimer S. Nagurney.
260 $aNew York, NY :$bSpringer New York :$bImprint: Springer,$c2013.
300 $aIX, 142 p. 25 illus.$bdigital.
490 0 $aSpringerBriefs in Optimization,$x2190-8354
505 0 $a​1. Introduction and Scope -- 2. Blood Supply Chains -- 3. Medical Nuclear Supply Chains -- 4. Food Supply Chains -- 5. Pharmaceutical Supply Chains -- 6. Fast Fashion Apparel Supply Chains -- References. .
520 $aDespite significant achievements, the discipline of supply chain management is still unable to satisfactorily handle many practical real-world challenges.  The authors of Networks Against Time claim that a unified supply chain network analytics framework is needed which should be able to handle optimization and competitive behavior while also maintain relevance to many industrial sectors in which perishable products are prominent, from healthcare to food and from fashion apparel to technology. This Brief provides a wide range of critical supply chain problems which are modeled as generalized networks. Guidelines are provided to determine the arc multipliers that capture perish ability of the product whether food, radioisotopes, or even highly perishable blood in healthcare over space and time. Through case studies the authors portray the application of the models and algorithms to real-world sectors which illustrate the power of the framework in practice. The models and algorithms are fully described along with the input and output data in the case studies. This level of transparency is useful pedagogically as well as for future research and for applications in practice. Researchers and practitioners in mathematics, in operations research and management science, operations management, as well as in economics and computer science will find this book useful to gain a broader appreciation of the richness of network supply chain structures, processes, and applications. This book can also be used by advanced undergraduate students and graduate students in the disciplines noted above to familiarize themselves with methodologies and supply chain network models and applications.​​
650 10 $aMathematics.
650 0 $aMathematics.
650 0 $aMathematical optimization.
650 24 $aOperations Research, Management Science.
650 24 $aGame Theory, Economics, Social and Behav. Sciences.
650 24 $aMathematical Modeling and Industrial Mathematics.
650 24 $aOptimization.
700 1 $aYu, Min.
700 1 $aMasoumi, Amir H.
700 1 $aNagurney, Ladimer S.
776 08 $iPrinted edition:$z9781461462767
830 0 $aSpringerBriefs in optimization.
988 $a20130202
906 $0VEN