Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function

Abstract

In a managerial position, the ultimate objective is to take the right decision for the decision maker (DM) when transportation parameters are uncertain due to the globalization and other uncontrollable influences. In this paper, fuzzy membership function tactic based on goal programming to obtain the desired compromise solution of a multi-objective transportation problem (MOTP) in uncertain environment is proposed where the DM can choose a confidence level for different parameters. On the basis of DM’s choice on a particular confidence level, a compromise solution is obtain indicating the satisfaction level of the DM if the problem is feasible for this chosen confidence level. Uncertain normal distribution is used to convert the parameters from uncertain to a certain one. Simple linear programming problem (LPP) is designed using fuzzy linear membership function where the upper and lower values of the objectives are the desired goals of the DM. A numerical illustration is furnished to establish the effectiveness of the designed model whereas the single objective transportation problems are solved by TORA and LPPs are solved by using LINGO for operations research.