[3] Vilenskiy P.L., Livshits V.N., Smolyak S.A. Otsenka effektivnosti investitsionnykh
proektov: teoriya i praktika [Evaluating the effectiveness of investment projects:
theory and practice]. Moscow, Delo Publ., 2008. 888 p.
[4] Levner E., Proth J.-M. Strategic management of ecosystems: A supply chain
perspective. Ch. 2.
Collect. Pap. “Strategic Management of Marine Ecosystems”
. Ed.
Levner E., Linkov I., Proth J.-M. NATO Science Series IV: Earth and Environmental
Series, Springer, 2005, vol. 50, pp. 95–107. DOI: 10.1007/1-4020-3198-X_6
[5] Ptuskin A.S., Levner E.V. Entropy approach to simplify of the supply chain structure
to select antirisk strategic decisions.
Ekonomicheskaya nauka sovremennoy Rossii
[Economic Science of Contemporary Russia], 2012, no. 4 (59), pp. 76–90 (in Russ.).
[6] White W.J., O’Connor A.C., Rowe B.R. Economic impact of inadequate
infrastructure for supply chain integration.
Final report RTI 07007.013
, National
Inst. of Standards and Technology, May, 2004.
[7] Jeeva A.S. Reducing supply risk caused by the stockwhip effect in supply chains.
Proc. 2011 International Conf. on Ind. Engin. And Operations Management
, 2011,
Kuala Lumpur (Malaysia), January 22–24, pp. 739–744.
[8] Karp A., Ronen B. Improving shop floor control: an entropy model approach.
Int. J.
Production Research
, 1992, vol. 30, no. 4, pp. 923–938.
[9] Martinez-Olvera C. Entropy as an assessment tool of supply chain information
sharing.
European J. Operational Research
, 2008, no. 185, pp. 405–417.
[10] Allesina S., Azzi A., Battini D., Regattieri A. Performance measurement in supply
chains: new network analysis and entropic indexes.
Int. J. Production Research
, 2010,
vol. 48 (8), pp. 2297–2321.
[11] Isik F. An Entropy-Based Approach for Measuring Complexity in Supply Chains.
Int. J. Production Research
, 2010, vol. 48, no. 12, pp. 3681–3696.
[12] Shannon C.E. A mathematical theory of communication.
The Bell System Tech. J.
,
1948, vol. 27 (3), pp. 379–423.
[13] Ingargiola G.P., Korsh J.F. Reduction algorithm for zero-one single knapsack
problems.
Management Science
, 2010, vol. 20 (4), part 1, pp. 460–463.
Статья поступила в редакцию 14.10.2013
Птускин Александр Соломонович — д-р экон. наук, профессор кафедры “Экономика
и организация производства” Калужского филиала МГТУ им. Н.Э. Баумана. Автор
92 научных работ в области экономико-математического моделирования, теории не-
четких множеств и ее применения в промышленности, бизнеса и финасов, страте-
гического управления, инвестиций, анализа рисков, искусственного интеллекта.
Калужский филиал МГТУ им. Н.Э. Баумана, Российская Федерация, 248000
г. Калуга, ул. Баженова, д. 2.
A.S. Ptuskin — Dr. Sci. (Econ.), professor of “Economics and Organization of Production”
department of the Kaluga Branch of the Bauman Moscow State Technical University.
Author of 92 publications in the field of economical and mathematical simulation, theory of
fuzzy sets and its applications in the industry, business and finance, strategic management,
investments, risk assessment, artificial intelligence, theory of scheduling, supply chain
management.
Kaluga Branch of the Bauman Moscow State Technical University, ul. Bazhenova 2,
Kaluga, 248000 Russian Federation.
Левнер Евгений — д-р философии, профессор Ашкелонского Академического
колледжа. Автор 88 научных работ в области экономико-математического моделиро-
вания, исследования операций, теории нечетких множеств, анализа рисков, теории
расписаний, управления цепями поставок.
Академический колледж, Израиль 78211, Ашкелон, ул. Бен-цви, 12.
E.V. Levner — PhD, Professor at the Ashkelon Academic College. Author of 88
publications in the field of economical and mathematical simulation, operations research,
theory of fuzzy sets, risk assessment, theory of scheduling, supply chain management.
Ashkelon Academic College, 12 Ben Zvi St., Ashkelon, 78211 Israel.
ISSN 0236-3941. Вестник МГТУ им. Н.Э. Баумана. Сер. “Машиностроение” 2014. № 3 135