This paper presents a two-phase interactive satisfying optimization method for fuzzy multiple objectives optimization with linguistic preference. This proposed approach utilizes the view that the more important objective has the higher desirable satisfying degree. The originally complex optimization problem is simplified and divided into two parts that are solved one by one. The decision maker can acquire satisfying solution of all the objectives under linguistic preference. Numerical example shows the efficiency, flexibility, and sensitivity of the proposed method.Multiple objectives optimization, linguistic preference, interactive, satisfying optimization
AbstractIn an earlier paper by the authors (J. Math. Anal, .4ppl.153, 1990, 97-111), the general mul...
© Springer Science + Business Media, LLC 2008. Multi-objective linear programming (MOLP) techniques ...
Some general concepts and ideas related to fuzzy optimization as, e.g., a fuzzy constraint, fuzzy go...
An interactive fuzzy multiple objective optimization method was proposed for solving fuzzy multiple ...
Generalizing our earlier results on optimization with linguistic variables [3, 6, 7] we introduce a ...
An enhanced two-step method via relaxed order of satisfactory degrees for fuzzy multiobjective optim...
This paper presents an interactive fuzzy goal programming approach to determine the preferred compro...
In this paper we present a problem of multicriterial optimization and different mod-els to solve it....
International Series in Operations Research & Management Science. ISBN: 978-1-4020-7128-7The roots o...
In many real-life design situations, there are several different criteria that we want to optimize, ...
AbstractGoal programming as a well known technique has been widely used for solving multi objective ...
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. We give an overview of interactive methods developed for solving nonlin-ear multiobjective...
Most real-life optimisation problems involve multiple objective functions.Finding a solution that sa...
AbstractIn an earlier paper by the authors (J. Math. Anal, .4ppl.153, 1990, 97-111), the general mul...
© Springer Science + Business Media, LLC 2008. Multi-objective linear programming (MOLP) techniques ...
Some general concepts and ideas related to fuzzy optimization as, e.g., a fuzzy constraint, fuzzy go...
An interactive fuzzy multiple objective optimization method was proposed for solving fuzzy multiple ...
Generalizing our earlier results on optimization with linguistic variables [3, 6, 7] we introduce a ...
An enhanced two-step method via relaxed order of satisfactory degrees for fuzzy multiobjective optim...
This paper presents an interactive fuzzy goal programming approach to determine the preferred compro...
In this paper we present a problem of multicriterial optimization and different mod-els to solve it....
International Series in Operations Research & Management Science. ISBN: 978-1-4020-7128-7The roots o...
In many real-life design situations, there are several different criteria that we want to optimize, ...
AbstractGoal programming as a well known technique has been widely used for solving multi objective ...
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. We give an overview of interactive methods developed for solving nonlin-ear multiobjective...
Most real-life optimisation problems involve multiple objective functions.Finding a solution that sa...
AbstractIn an earlier paper by the authors (J. Math. Anal, .4ppl.153, 1990, 97-111), the general mul...
© Springer Science + Business Media, LLC 2008. Multi-objective linear programming (MOLP) techniques ...
Some general concepts and ideas related to fuzzy optimization as, e.g., a fuzzy constraint, fuzzy go...