Multi-objective programming became more and more popular in real world decision making problems in recent decades. There is an underlying and fundamental uncertainty in almost all of these problems. Among different frameworks of dealing with uncertainty, probability and statistic-based schemes are well-known. In this paper, a method is developed to find some efficient solutions of a multi-objective stochastic programming problem. The method composed a process of transforming the stochastic multi-objective problem to a bi-objective equivalent using the concept of Chebyshev inequality bounds and then solving the obtained problem with a fuzzy set based approach. Application of the proposed method is examined on two numerical examples and the r...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) prob...
For multi-objective optimization problems, a common solution methodology is to determine a Pareto op...
Multi-objective programming became more and more popular in real world decision making problems in r...
This study focuses on solving multiobjective stochastic linear programming (MSLP) problems with part...
This paper deals with the multi-objective chance constrained programming, where the right hand side ...
In this thesis, the value of modeling uncertainty in multi-objective problems is inves-tigated. Firs...
This paper proposes an approach where it can be applied to the optimization decisions making problem...
We study a class of stochastic bi-criteria optimization problems with one quadratic and one linear ...
Two major approaches to deal with randomness or impression involved in mathematical programming prob...
In this paper we suggest an approach for solving a multiobjective stochastic linear programming prob...
AbstractStochastic multi objective programming problems commonly arise in complex systems such as po...
The problems of linear programming are developing from time to time, and its complexity is constantl...
In this paper, we focus on multiobjective 0-1 programming problems under the situation where stochas...
Probabilistic or Stochastic programming is a framework for modeling optimization problems that invol...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) prob...
For multi-objective optimization problems, a common solution methodology is to determine a Pareto op...
Multi-objective programming became more and more popular in real world decision making problems in r...
This study focuses on solving multiobjective stochastic linear programming (MSLP) problems with part...
This paper deals with the multi-objective chance constrained programming, where the right hand side ...
In this thesis, the value of modeling uncertainty in multi-objective problems is inves-tigated. Firs...
This paper proposes an approach where it can be applied to the optimization decisions making problem...
We study a class of stochastic bi-criteria optimization problems with one quadratic and one linear ...
Two major approaches to deal with randomness or impression involved in mathematical programming prob...
In this paper we suggest an approach for solving a multiobjective stochastic linear programming prob...
AbstractStochastic multi objective programming problems commonly arise in complex systems such as po...
The problems of linear programming are developing from time to time, and its complexity is constantl...
In this paper, we focus on multiobjective 0-1 programming problems under the situation where stochas...
Probabilistic or Stochastic programming is a framework for modeling optimization problems that invol...
Abstract—In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stoch...
In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) prob...
For multi-objective optimization problems, a common solution methodology is to determine a Pareto op...