Add to ORKGAfter Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there have been many successful applications of this optimization. However, in many practical situations, it turns out to be more efficient to precisiate the objective function before performing optimization. In this paper, we provide a possible explanation for this empirical fact
In many cases, we need to select the best of the possible alternatives, but we do not know for sure ...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Abstract—After Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there...
a function under fuzzy constraints, there have been many successful applications of this optimizatio...
a function under fuzzy constraints, there have been many successful applications of this optimizatio...
An efficient iterative heuristic algorithm has been used to implement Bellman-Zadeh solution to the ...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
In many practical situations, we need to optimize the objective function under fuzzy constraints. Fo...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
In many cases, we need to select the best of the possible alternatives, but we do not know for sure ...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Abstract—After Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there...
a function under fuzzy constraints, there have been many successful applications of this optimizatio...
a function under fuzzy constraints, there have been many successful applications of this optimizatio...
An efficient iterative heuristic algorithm has been used to implement Bellman-Zadeh solution to the ...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
In many practical situations, we need to optimize the objective function under fuzzy constraints. Fo...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
In many cases, we need to select the best of the possible alternatives, but we do not know for sure ...
Many practical optimization problems are characterized by some flexibility in the problem constraint...
Many practical optimization problems are characterized by some flexibility in the problem constraint...