Add to ORKG1 Introduction Optimization and decision making are important. In many industrial engineering problems, we must select a design, select parameters of a process, or, in general, make a decision. Informally, this decision must be optimal, the best for the users. In traditional operations research, we assume that we know the objective function f (x) whose values describe what is best for the users. 2 Hung T. Nguyen and Vladik Kreinovich For example, for a chemical plant, this function f (x) may represent the profit resulting from using parameters x
In optimization, it is used to deal with uncertain and inaccurate factors which make difficult the a...
In practice, it is often necessary to make a decision under uncertainty. In the case of interval unc...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...
In many industrial engineering problems, we must select a design, select parameters of a process, or...
Abstract—After Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there...
AbstractResults of research into the use of fuzzy sets for handling various forms of uncertainty in ...
Optimization is of central concern to a number of discip lines. Operations Research and Decision Th...
Traditional decision theory is based on a simplifying assumption that for each two alternatives, a u...
In many situations, e.g., in financial and economic decision making, the decision results either in ...
The deterministic optimization models for chemical processes assume perfect information, i.e., the s...
Uncertainty in parameters, which are assumed to be known and do not change their values during the c...
In many practical situations, we know the exact form of the objective function, and we know the opti...
The parameters of real-world optimization problems are often uncertain due to the failure of exact e...
In many engineering problems, to estimate the desired quantity, we process measurement results and e...
Covering in detail both theoretical and practical perspectives, this book is a self-contained and sy...
In optimization, it is used to deal with uncertain and inaccurate factors which make difficult the a...
In practice, it is often necessary to make a decision under uncertainty. In the case of interval unc...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...
In many industrial engineering problems, we must select a design, select parameters of a process, or...
Abstract—After Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there...
AbstractResults of research into the use of fuzzy sets for handling various forms of uncertainty in ...
Optimization is of central concern to a number of discip lines. Operations Research and Decision Th...
Traditional decision theory is based on a simplifying assumption that for each two alternatives, a u...
In many situations, e.g., in financial and economic decision making, the decision results either in ...
The deterministic optimization models for chemical processes assume perfect information, i.e., the s...
Uncertainty in parameters, which are assumed to be known and do not change their values during the c...
In many practical situations, we know the exact form of the objective function, and we know the opti...
The parameters of real-world optimization problems are often uncertain due to the failure of exact e...
In many engineering problems, to estimate the desired quantity, we process measurement results and e...
Covering in detail both theoretical and practical perspectives, this book is a self-contained and sy...
In optimization, it is used to deal with uncertain and inaccurate factors which make difficult the a...
In practice, it is often necessary to make a decision under uncertainty. In the case of interval unc...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...