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Fuzzy Sets and Interactive Multiobjective Optimization

is significant to realize that multiple objectives are often noncom mensurable and conflict with each other in multiobjective optimization problems. With;

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Pseudolinear Functions and Optimization

-pseudolinear functions to pseudolinear and n-pseudolinear fuzzy mappings and characterizations of solution sets of pseudolinear fuzzy optimization;

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Pseudolinear Functions and Optimization

-pseudolinear functions to pseudolinear and n-pseudolinear fuzzy mappings and characterizations of solution sets of pseudolinear fuzzy optimization;

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Multiple Criteria Decision Analysis

). Part V looks at Non-Classical MCDA Approaches, with chapters on risk and uncertainty in MCDA, the decision rule approach to MCDA, the fuzzy;

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Interactive Multiobjective Decision Making Under Uncertainty

considered. In Chapter 3, multiobjective programming problems with fuzzy random variables are formulated, and the corresponding interactive;

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Interactive Multiobjective Decision Making Under Uncertainty

considered. In Chapter 3, multiobjective programming problems with fuzzy random variables are formulated, and the corresponding interactive;

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Nonlinear Multiobjective Optimization

optimization which is theoretically well-founded and numerically efficient. The power of the new method is demonstrated by solving two real-life;

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Fuzzy Probabilities and Fuzzy Sets for Web Planning

service rates to model the fuzzy queuing system in part three in Chapters 11 and 12. Optimization models comprise part four in Chapters 13-17. The;

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Multiobjective Optimization

date no one has presented a book which unifies the two. That is the aim of Multiobjective Optimization: Behavioural and Computational;

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Multicriteria DecisionMaking Under Conditions of Uncertainty

on the topic-and their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods;

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Nonlinear Multiobjective Optimization

Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making;

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Water Resources Systems

principles of hydrology, hydraulics and probability together with optimization techniques and economic analysis are covered. The subject is developed;

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Fuzzy and Multi-Level Decision Making

-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these;

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Data Envelopment Analysis with R

data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how;

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Data Envelopment Analysis with R

data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how;

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Computational Intelligence in Expensive Optimization Problems

such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such;

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Multiobjective Optimization Methodology

The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach;

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Multiobjective Optimization Methodology

The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach;

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Fuzzy Sets-Based Methods and Techniques for Modern Analytics

-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a;

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Genetic Algorithms And Engineering Optimization

, and genetic optimizations-and to show how GAs can be used to solve an array of constrained, combinatorial, multiobjective, and fuzzy;

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An Introduction to Fuzzy Sets

An Introduction to Fuzzy Sets provides a comparison of the quality of life in urban, intermediate and rural NUTS III regions in Portugal;

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Thermodynamic Analysis and Optimization of Geothermal Power Plants

Thermodynamic Analysis and Optimization of Geothermal Power Plants guides researchers and engineers on the analysis and optimization;

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Solving Optimization Problems with MATLAB (R)

This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied;

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Fuzzy Information Measures with Applications

FUZZY INFORMATION MEASURES WITH APPLICATIONS consists from chapters 1 to 8 deals with fuzzy sets theory including fuzzy sets and operations;

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A+BE Architecture and the Built Environment - Design as ­Exploration

is formulated, or partially formulated, as an optimization problem. Multi-Disciplinary Optimization and Multi-Objective Optimization, as two important;

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Fuzzy Lie Algebras

This book explores certain structures of fuzzy Lie algebras, fuzzy Lie superalgebras and fuzzy n-Lie algebras. In addition, it applies;

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Deep Neuro-Fuzzy Systems with Python

relations, and fuzzy inference Review neural networks, back propagation, and optimization Work with different architectures such as Takagi-Sugeno;

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