This paper proposes the method to the solution of multi objective linear programming problems in fuzzy environment. Here attention has been paid to the study of optimal compromise solution for multi objective fuzzy linear programming problems. Two algorithms have been presented to gives efficient solutions as well as an optimal compromise solution. An illustrative example is given to describe o...

This study proposes a new multi-item inventory model with hybrid cost parameters under a fuzzy-stochastic constraint and permissible delay in payment. The price and marketing expenditure dependent stochastic demand and the demand dependent the unit production cost are considered. Shortages are allowed and partially backordered. The main objective of this paper is to determine selling price, mar...

This paper proposes a new algorithm for the solution of fully fuzzy Multi objective linear programming problems involving triangular fuzzy number without converting them to equivalent classical problems. Based on the fuzzy ideal and fuzzy negative ideal solution of each single fuzzy objective function we propose an algorithm which provides a fuzzy Pareto-optimal solution for the given fully fuz...

Abstract: This paper investigates a multi-objective supplier selection and order allocation problem under quantity discounts in a fuzzy environment. Prior research on supplier selection and order allocation with quantity discounts mainly considered partial fuzziness of the decision problem; a situation where both the objectives of the decision maker and the constraints are fuzzy has not been st...

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

Planning of sewer systems typically involves limitations and problems, regardless whether traditional planning methods or optimization models are used. Such problems include non-quantifiability, fuzzy objectives, uncertainties in decision-making variables which commonly applied the any process. Particularly, have prevented inclusion these models. Consequently, theoretical optional solution math...