Fuzzy Multi-Objective Transfer Problem Using Genetic Algorithm

Therefore, planning and designing transmission networks is a fundamental topic in various scientific disciplines, including industrial and civil engineering. The Transfer Model (TM) constitutes a specific class of linear programming problems that addresses situations where goods are transported from sources (such as factories) to destinations (such as warehouses). This method combines fuzzy logic and genetic algorithms to enhance the design process. Goals are normalized using a multi-objective fuzzy method, enabling adjustment to function as a factor of the final objective function. The proposed genetic algorithm's evaluation necessitated a predetermined number of generations, which in this case was set to 12 generations. Upon analyzing these generations, it became evident that the algorithm converges to a nearly perfect solution. Consequently, the researcher conducted a special case study within a real production unit, specifically a meat production company, demonstrating favorable performance of the proposed model. The model comprises three main components: reducing travel distances between customers, minimizing distances between customers and the warehouse, and mitigating penalties for unmet customer demands. This paper presents an innovative and effective approach to address transmission network design based on reliability criteria. The results indicate an improvement in balancing task complexity and reducing overall path costs compared to similar methods. Overall, the findings demonstrate the superiority of the proposed algorithm over traditional methods in resolving problems of varying dimensions.