This paper is devoted to study the multiobjective system programming under the assumption that some of the problem parameters are random variables. A method called Interactive Reference Goal Satisfied Degree and Feasi...This paper is devoted to study the multiobjective system programming under the assumption that some of the problem parameters are random variables. A method called Interactive Reference Goal Satisfied Degree and Feasible Degree (IRGSD-FD) is developed to solve stochastic multiobjective problems. It is an interactive method providing a so-called `dialogue' between the user and the model, the decision maker having the option conducting the search process for the (α, β)-efficient solutions by modifying the initial conditions according to the partial results obtained. During the iterations, the decision maker can improve upon the reference goal or called aspiration level already attained by one objective function as well as upon the probability of reaching the corresponding objective or called satisfied degree (or both), or/and the probability of satisfying the constraint or called feasible degree already attained by the constraint. Finally, the application of IRGSD-FD method in the resource allocation problem is discussed with a case study for project investment management.展开更多
文摘This paper is devoted to study the multiobjective system programming under the assumption that some of the problem parameters are random variables. A method called Interactive Reference Goal Satisfied Degree and Feasible Degree (IRGSD-FD) is developed to solve stochastic multiobjective problems. It is an interactive method providing a so-called `dialogue' between the user and the model, the decision maker having the option conducting the search process for the (α, β)-efficient solutions by modifying the initial conditions according to the partial results obtained. During the iterations, the decision maker can improve upon the reference goal or called aspiration level already attained by one objective function as well as upon the probability of reaching the corresponding objective or called satisfied degree (or both), or/and the probability of satisfying the constraint or called feasible degree already attained by the constraint. Finally, the application of IRGSD-FD method in the resource allocation problem is discussed with a case study for project investment management.
