In this paper a fuzzy programming technique is presented to solve multiobjective chance constrained programming problem having the right sided parameters associated with system constrains follow log-normal distribution. In model formulation process the imprecise probabilistic problem is converted into an equivalent fuzzy programming model by applying chance constrained programming methodology. Then by considering fuzzy nature of parameters involved with the system constraints, the problem is decomposed on the basis of tolerance values of the parameters. The individual optimal value of each objective is found to construct the membership goals of the objectives. A priority based fuzzy goal programming approach is used for achievement of the highest membership degree to the extent possible under different priority structures to achieve the ideal point dependent solution in the decision making context. To expound the potentiality of the proposed approach, an illustrative example is solved and the solution is compared with other existing technique.