| 000 | 03330cam a2200421 i 4500 | ||
|---|---|---|---|
| 999 |
_c4167 _d4167 |
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| 001 | 17756024 | ||
| 005 | 20180623095013.0 | ||
| 008 | 130529s2014 flua b 001 0 eng | ||
| 010 | _a 2013014250 | ||
| 020 | _a9781466554610 (hardback : acidfree paper) | ||
| 040 |
_aDLC _beng _cDLC _erda _dDLC |
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| 042 | _apcc | ||
| 050 | 0 | 0 |
_aT57.95 _b.T938 2014 |
| 082 | 0 | 0 |
_a658.4033 _223 |
| 084 |
_aBUS049000 _aMAT003000 _aTEC009000 _2bisacsh |
||
| 100 | 1 |
_aTzeng, Gwo-Hshiung, _eauthor. |
|
| 245 | 1 | 0 |
_aFuzzy multiple objective decision making / _cGwo-Hshiung Tzeng, Jih-Jeng Huang. |
| 250 | _a1st ed. | ||
| 260 |
_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c2014. |
||
| 264 | 1 |
_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c[2014] |
|
| 300 |
_axiv, 308 pages : _billustrations ; _c24 cm |
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| 336 |
_atext _2rdacontent |
||
| 337 |
_aunmediated _2rdamedia |
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| 338 |
_avolume _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _a"Preface Operations research has been adapted by management science scholoars to manage realistic problems for a long time. Among these methods, mathematical programming models play a key role in optimizing a system. However, traditional mathematical programming focuses on single-objective optimization rather than multi-objective optimization as we encounter in real situation. Hence, the concept of multi-objective programming was proposed by Kuhn, Tucker and Koopmans in 1951 and since then became the main-stream of mathematical programming. Multi-objective programming (MOP) can be considered as the natural extension of single-objective programming by simultaneously optimizing multi-objectives in mathematical programming models. However, the optimization of multi-objectives triggers the issue of the Pareto solutions and complicates the derived answer. In addition, more scholars incorporate the concepts of fuzzy sets and evolutionary algorithms to multi-objective programming models and enrich the field of multi-objective decision making (MODM). The content of this book is divided into two parts: methodologies and applications. In the first part, we introduced most popular methods which are used to calculate the solution of MOP in the field of MODM. Furthermore, we included three new topics of MODM: multi-objective evolutionary algorithms (MOEA), expanding De Novo programming to changeable spaces, including decision space and objective space, and network data envelopment analysis (NDEA) in this book. In the application part, we proposed different kind of practical applications in MODM. These applications can provide readers the insights for better understanding the MODM with depth. "-- | ||
| 650 | 0 | _aMultiple criteria decision making. | |
| 650 | 0 | _aFuzzy sets. | |
| 650 | 0 | _aManagement science. | |
| 650 | 7 |
_aBUSINESS & ECONOMICS / Operations Research. _2bisacsh |
|
| 650 | 7 |
_aMATHEMATICS / Applied. _2bisacsh |
|
| 650 | 7 |
_aTECHNOLOGY & ENGINEERING / Engineering (General). _2bisacsh |
|
| 700 | 1 |
_aHuang, Jih-Jeng, _eauthor. |
|
| 856 | 4 | 2 |
_3Cover image _uhttp://images.tandf.co.uk/common/jackets/websmall/978146655/9781466554610.jpg |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2ddc _cBK |
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