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" Rough multiple objective decision making "
Jiuping Xu, Zhimiao Tao.
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BL
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| Record Number
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730091
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b549850
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| Main Entry
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Jiuping Xu, Zhimiao Tao.
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| Title & Author
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Rough multiple objective decision making\ Jiuping Xu, Zhimiao Tao.
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| Publication Statement
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Boca Raton, FL: CRC/Chapman & Hall, 2012
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| Page. NO
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(xvii, 428 p. ) : ill.
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| ISBN
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0429063202
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: 128331178X
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: 1439872368
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: 6613311782
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: 9780429063206
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: 9781283311786
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: 9781439872369
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: 9786613311788
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| Notes
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Formerly CIP.;Rough Set Theory Basic concepts and properties of rough sets Rough Membership Rough Intervals Rough Function Applications of Rough Sets Multiple Objective Rough Decision Making Reverse Logistics Problem with Rough Interval Parameters MODM based Rough Approximation for Feasible Region EVRM CCRM DCRM Reverse Logistics Network Design Problem of Suji Renewable Resource Market Bilevel Multiple Objective Rough Decision Making Hierarchical Supply Chain Planning Problem with Rough Interval Parameters Bilevel Decision Making Model BL-EVRM BL-CCRM BL-DCRM Application to Supply Chain Planning of Mianyang Co., Ltd Stochastic Multiple Objective Rough Decision Multi-Objective Resource-Constrained Project Scheduling Under Rough Random Environment Random Variable Stochastic EVRM Stochastic CCRM Stochastic DCRM Multi-Objective rc-PSP/mM/Ro-Ra for Longtan Hydropower Station Fuzzy Multiple Objective Rough Decision Making Allocation Problem under Fuzzy Environment Fuzzy Variable Fu-EVRM Fu-CCRM Fu-DCRM Earth-Rock Work Allocation Problem
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| Contents
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Elements of rough set theory --;Multiple objective rough decision making --;Bilevel multiple objective rough decision making --;Random multiple objective rough decision making --;Fuzzy multiple objective rough decision making --;Methodological system for RMODM.
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| Abstract
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This text applies rough set theory and rough approximation technique to real-world multiple objective decision making problems. The authors present several techniques in rough approximation and apply them to case studies in engineering, such as particle swarms and transportation.Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory. Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques-and some that employ simulation-based intelligent algorithms-to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions. Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research. Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory. Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques-and some that employ simulation-based intelligent algorithms-to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions. Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research.
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| Subject
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Mathematical statistics.
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| Subject
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Multiple criteria decision making.
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| LC Classification
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QA279.4J587 2012
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| Added Entry
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Jiuping Xu
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Zhimiao Tao
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