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Original research GENETIC ALGORITHM OPTIMIZATION OF FACILITY LAYOUTS FOR MANUFACTURING RESILIENCE UNDER DEMAND UNCERTAINTY A SENSITIVITY ANALYSIS STUDYPages 305-314 Abstract
The focus of this research paper is on the role of facility layout design influencing manufacturing effectiveness, efficiency, and throughput in uncertain environments. A genetic algorithm-based model has been proposed for optimizing the layout design of a bottled water manufacturing plant with the aim of minimizing material handling costs and increasing efficiency and throughput. Department level location arrangement, material flow association, Manhattan distance, and evolutionary algorithms have been used for designing the optimal layout within a python-based simulation platform. System sensitivity has been analyzed with respect to different levels of demand in the system. The results suggest a significant decrease in material handling costs from 26,500 to 10,600, which is 60% lower than the current scenario. Moreover, the Throughput Index increased from 3.77 to 9.43, indicating a 150% increase in system efficiency and resilience under uncertainty.
Keywords:
Facility Layout Planning; Genetic Algorithm; Disruption; Supply Chain Resilience; Uncertainty.
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Bright Osagie Eze 
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