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Synopsis
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.
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Synopsis
This monograph is the first to integrate ambiguous parameters in problem-formulation with fuzzy goals for multiobjective optimization into a unified methodology. Including "real-world" applications illustrated by interactive computer programs (written in C, version 6.0 for IBM PCs), the work is intended for advanced undergraduate and graduate students and specialists in systems analysis in such fields as public decision-making, administrative planning, and managerial decision-making.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date1993
- ISBN 10 0306443376
- ISBN 13 9780306443374
- BindingHardcover
- LanguageEnglish
- Number of pages320
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FUZZY SETS AND INTERACTIVE MULTIOBJECTIVE OPTIMIZATION
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Plenum Publishing Corporation, New York City, 1993
ISBN 10: 0306443376
ISBN 13: 9780306443374
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Hardcover. First Edition. Octavo, ix, 308 pages. In Very Good minus condition. Spine dark turquoise with white lettering. Boards have mild finger staining, front board has small cut, front and rear board corners have mild wear, and spine head and tail have light wear. Textblock rear end paper has small indent from floppy disk and tail edge has small pencil line. Rear pastedown has floppy disk in slip case attached with adhesive. Shelved in ND-E. 1378165. FP New Rockville Stock. Seller Inventory # 1378165
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Fuzzy Sets and Interactive Multiobjective Optimization (Applied Information Technology)
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Fuzzy Sets and Interactive Multiobjective Optimization (Applied Information Technology)
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Fuzzy Sets and Interactive Multiobjective Optimization
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 324 pp. Englisch. Seller Inventory # 9780306443374
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Fuzzy Sets and Interactive Multiobjective Optimization
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Fuzzy Sets and Interactive Multiobjective Optimization
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Springer US, Springer New York, 1993
ISBN 10: 0306443376
ISBN 13: 9780306443374
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9780306443374
Quantity: 1 available