LITERATURE REVIEW ON IMPLEMENTATION OF INTUITIONISTIC FUZZY SET USING ANALYTICAL HIERARCHY PROCESS (AHP) FOR FOOD MANUFACTURING INDUSTRY BASED ON MULTI-FACTORS

This literature review explores of Analytical Hierarchical Process (AHP) application in conjunction with Intuitionistic Fuzzy Sets (IFS) as a powerful decision-making framework within the context of the food manufacturing industry. The review synthesizes a wide array of research contributions and findings to provide insights into the dynamic and uncertain nature of this industry. The study reveals that the AHP-IFS methodology offers a structured approach to address the complexities inherent in the food manufacturing sector, which undergoes distinct phases from inception to maturity, and potentially, decline or renewal. Decision criteria and factors, including market dynamics, technological advancements, regulatory compliance, sustainability concerns, and financial considerations, are analyzed and prioritized using AHP-IFS, considering their interdependencies and uncertainties. Strategic planning, resource allocation, and competitive analysis within the industry have been significantly enhanced through the application of this methodology. Moreover, as sustainability and environmental issues become increasingly important, AHP-IFS is also employed to evaluate the environmental impact of business decisions, aligning with global efforts to promote sustainability. Challenges associated with data availability and computational complexities have been acknowledged, but the potential for refinement and expansion of the methodology, including the incorporation of machine learning techniques, offers promising avenues for future research. Ultimately, AHP-IFS stands as a valuable tool to guide informed decision-making processes throughout the ever-evolving business life cycle of the food manufacturing industry, ensuring adaptability and competitiveness in a complex and uncertain landscape.