MODELING AND SOLVING PRODUCTION PLANNING PROBLEMS WITH FUZZY GOAL PROGRAMMING: A CASE STUDY

Abstract

In modern manufacturing environments, decision making often involves navigating conflicting objectives, uncertain data, and resource limitations. This paper presents a comprehensive approach to optimizing production planning using a Fuzzy Goal Programming

(FGP) model, applied to a real-world case study of a plastic water tank manufacturing facility. The proposed model addresses six key production goals: maximizing output, minimizing costs, labor hours, material consumption, defective rates, and storage usage. Unlike traditional models that rely on fixed, precise goals, the FGP framework accommodates uncertainty through triangular fuzzy membership functions, enabling more realistic and flexible planning. Using actual factory data, the model was implemented in a linear programming environment and validated through collaboration with technical staff. Results demonstrate the model's practical effectiveness in generating balanced and feasible production strategies that closely align with operational aspirations while managing trade-offs among competing objectives. This study underscores the potential of fuzzy multi-objective optimization as a powerful tool for decision support in uncertain, resource-constrained manufacturing contexts.