<p>A multi-objective linear programming problem addresses the complexities that arise in most practical decision-making scenarios. Such problems are crucial in various practical applications where multiple conflicting objectives must be optimized simultaneously. However, traditional optimization methods struggle to effectively manage uncertainty and vagueness. To address these shortcomings, hesitant fuzzy set theory was introduced. This theory allows decision-makers to express the uncertainty about the exact belongingness of an element in a set, accommodating imprecision and ambiguity. Additionally, the VIKOR method, which is a well-established multi-criteria decision-making technique, that has been used to identify a compromise solution among multiple conflicting objectives. In this study, we propose a bi-phase modified VIKOR method to solve multi-objective programming problems within hesitant fuzzy environment. The applicability and effectiveness of the developed methodology are demonstrated with a popular production planning problem. To validate results, the outcomes of the proposed methodology are compared with the various existing methods, highlighting the robustness and efficacy of the developed methodology.</p>