A mathematical framework of optimal agriculture planning via MCDM approach.
Loading...
Date
2024-07-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
UMT Lahore
Abstract
Agriculture undoubtedly plays a profound and irreplaceable role in the economy of Pakistan, being the cornerstone of livelihood that not only ensures food security for the nation but also serves as the main source of employment for countless people in various regions. The importance of the sector is further emphasized by its significant contribution to export earnings, which supports the stability and growth of Pakistan's economy. In addition, agriculture is an important livelihood for rural communities, providing essential livelihood support and acting as a catalyst for poverty alleviation across the country. In light of the evolving agricultural landscape, plant selection decision-making has emerged as a critical issue that requires increased attention and strategic planning to maximize productivity and sustainable results. This trend underlines the increasing complexity and importance of agricultural practices in Pakistan, highlighting the need for informed decisions and innovative approaches to improve the overall efficiency of the sector and the economic impact of the country. In light of our plant selection study, extensive mathematical modeling was used to delve into the complexity of this real-world challenge. This comprehensive analysis paved the way for the formulation of a multi-criteria decision making (MCDM) framework that sheds light on various aspects of the problem at hand. A combination of survey data and information from various online sources was carefully collected to gather the data needed for this study. As a result of extensive research and scientific work, a decision matrix was created that provides valuable insights into the collected data. In this study, advanced multi-criteria decision-making tools such as fuzzy TOPSIS were used to explore different options and accurately evaluate the criteria affecting crop selection. The area of operations research that encompasses MCDM methodologies is primarily concerned with the careful evaluation, comparative ranking and final selection of alternatives based on a number of different and often conflicting criteria. In this case, MCDM methodology is applied using Analytic Hierarchy Process (AHP) with TOPSIS techniques. The use of AHP precisely determines the relative weight of criteria, while the TOPSIS method effectively ranks alternatives according to their effectiveness against established standards. Programming techniques abstract xv are judiciously applied to analyze the results and determine the most appropriate crop for a given scenario. Optimal agricultural planning in Kasur, Pakistan requires a thorough evaluation of crop choices, resource allocation and sustainability factors on a one-abstract xvi hectare plot of land. The main objective is to maximize productivity while ensuring efficient use of resources and long-term environmental sustainability. Agriculture plays a crucial role in food security and environmental management, which emphasizes the importance of agricultural productivity and sustainability. The research focuses on the development of an adapted agricultural plan for a one-hectare plot of land in Kasur, Pakistan. The goal is to optimize productivity through efficient allocation of resources and promote long-term environmental health. The evaluation process includes a number of different aspects such as crop selection, resource allocation considerations and sustainability metrics such as water supply, soil quality maintenance and biodiversity conservation. Combining a multi-objective optimization approach, the research aims to find the ideal crop mix, irrigation schedule and fertilizer application strategy that together promote maximum productivity and sustainability. Ultimately, the results will be a valuable blueprint for smallholder farmers in Kasur, providing them with the tools they need to improve agricultural practices, improve economic prospects, and create a more active and sustainable food system within the region.