This paper presents the production planning problem in industry with different operational constraints, including strategic aim of the company, profit goal, limit on finishing and furnace hours needed, cups manufactured with target values being imprecise in nature. The fuzzy goal programming techniques is applied to maximize the production capacity, maximize the profit, minimize the extra finishing labor and furnace hours, and ensure the manufacturing capacity. The objective of this paper is to elaborate a plan which takes manager's preferences into account. The results illustrate the flexibility of the proposed model by adjusting goal priorities with respect to importance of each objective and the aspiration level with respect to desired target values. LINDO 14.0 optimizer solver is used to draw results of the problem.

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This paper presents a multi-objective fuzzy chance constrained capacitated transportation problem based on fuzzy goal programming problem with capacity restrictions on commodities which are shipped from different sources to different destinations. The capacity of each origin and the demand of each destination are considered random in nature with fuzzy normal stochastic parameters following normal distribution with fuzzy mean and fuzzy variance respectively. These inequality constraints are also considered as fuzzy probabilistic in nature assuming to be triangular fuzzy numbers. Further, the supply and demand constraints are converted into equivalent deterministic forms. Then, we define the fuzzy goal tolerance limit of each of the objective functions which are then characterized by the associated membership functions. In the solution process, the fuzzy parameters are defuzzied by applying graded mean integration method which provided a satisfactory result. Further, an illustrative example is solved to demonstrate the effectiveness of the proposed model.