Fuzzy Sets and Interactive Multiobjective Optimization:
The main characteristics of the real-world decision-making problems facing humans today are multidimensional and have multiple objectives including eco nomic, environmental, social, and technical ones. Hence, it seems natural that the consideration of many objectives in the actual decision-making p...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1993
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| Schriftenreihe: | Applied Information Technology
|
| Schlagworte: | |
| Online-Zugang: | BTU01 URL des Erstveröffentlichers |
| Zusammenfassung: | The main characteristics of the real-world decision-making problems facing humans today are multidimensional and have multiple objectives including eco nomic, environmental, social, and technical ones. Hence, it seems natural that the consideration of many objectives in the actual decision-making process re quires multiobjective approaches rather than single-objective. One ofthe major systems-analytic multiobjective approaches to decision-making under constraints is multiobjective optimization as a generalization of traditional single-objective optimization. Although multiobjective optimization problems differ from single objective optimization problems only in the plurality of objective functions, it is significant to realize that multiple objectives are often noncom mensurable and conflict with each other in multiobjective optimization problems. With this ob servation, in multiobjective optimization, the notion of Pareto optimality or effi ciency has been introduced instead of the optimality concept for single-objective optimization. However, decisions with Pareto optimality or efficiency are not uniquely determined; the final decision must be selected from among the set of Pareto optimal or efficient solutions. Therefore, the question is, how does one find the preferred point as a compromise or satisficing solution with rational pro cedure? This is the starting point of multiobjective optimization. To be more specific, the aim is to determine how one derives a compromise or satisficing so lution of a decision maker (DM), which well represents the subjective judgments, from a Pareto optimal or an efficient solution set |
| Beschreibung: | 1 Online-Ressource (XII, 308 p) |
| ISBN: | 9781489916334 |
| DOI: | 10.1007/978-1-4899-1633-4 |
Internformat
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Datensatz im Suchindex
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| author | Sakawa, Masatoshi |
| author_facet | Sakawa, Masatoshi |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 510 - Mathematics |
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| dewey-search | 510 |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4899-1633-4 |
| format | Electronic eBook |
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| id | DE-604.BV045186927 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:58Z |
| institution | BVB |
| isbn | 9781489916334 |
| language | English |
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| spelling | Sakawa, Masatoshi Verfasser aut Fuzzy Sets and Interactive Multiobjective Optimization by Masatoshi Sakawa Boston, MA Springer US 1993 1 Online-Ressource (XII, 308 p) txt rdacontent c rdamedia cr rdacarrier Applied Information Technology The main characteristics of the real-world decision-making problems facing humans today are multidimensional and have multiple objectives including eco nomic, environmental, social, and technical ones. Hence, it seems natural that the consideration of many objectives in the actual decision-making process re quires multiobjective approaches rather than single-objective. One ofthe major systems-analytic multiobjective approaches to decision-making under constraints is multiobjective optimization as a generalization of traditional single-objective optimization. Although multiobjective optimization problems differ from single objective optimization problems only in the plurality of objective functions, it is significant to realize that multiple objectives are often noncom mensurable and conflict with each other in multiobjective optimization problems. With this ob servation, in multiobjective optimization, the notion of Pareto optimality or effi ciency has been introduced instead of the optimality concept for single-objective optimization. However, decisions with Pareto optimality or efficiency are not uniquely determined; the final decision must be selected from among the set of Pareto optimal or efficient solutions. Therefore, the question is, how does one find the preferred point as a compromise or satisficing solution with rational pro cedure? This is the starting point of multiobjective optimization. To be more specific, the aim is to determine how one derives a compromise or satisficing so lution of a decision maker (DM), which well represents the subjective judgments, from a Pareto optimal or an efficient solution set Mathematics Mathematics, general Computer Science, general Computer science Fuzzy-Menge (DE-588)4061868-7 gnd rswk-swf Fuzzy-Menge (DE-588)4061868-7 s 1\p DE-604 Erscheint auch als Druck-Ausgabe 9781489916358 https://doi.org/10.1007/978-1-4899-1633-4 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Sakawa, Masatoshi Fuzzy Sets and Interactive Multiobjective Optimization Mathematics Mathematics, general Computer Science, general Computer science Fuzzy-Menge (DE-588)4061868-7 gnd |
| subject_GND | (DE-588)4061868-7 |
| title | Fuzzy Sets and Interactive Multiobjective Optimization |
| title_auth | Fuzzy Sets and Interactive Multiobjective Optimization |
| title_exact_search | Fuzzy Sets and Interactive Multiobjective Optimization |
| title_full | Fuzzy Sets and Interactive Multiobjective Optimization by Masatoshi Sakawa |
| title_fullStr | Fuzzy Sets and Interactive Multiobjective Optimization by Masatoshi Sakawa |
| title_full_unstemmed | Fuzzy Sets and Interactive Multiobjective Optimization by Masatoshi Sakawa |
| title_short | Fuzzy Sets and Interactive Multiobjective Optimization |
| title_sort | fuzzy sets and interactive multiobjective optimization |
| topic | Mathematics Mathematics, general Computer Science, general Computer science Fuzzy-Menge (DE-588)4061868-7 gnd |
| topic_facet | Mathematics Mathematics, general Computer Science, general Computer science Fuzzy-Menge |
| url | https://doi.org/10.1007/978-1-4899-1633-4 |
| work_keys_str_mv | AT sakawamasatoshi fuzzysetsandinteractivemultiobjectiveoptimization |