Article Preview
Top1. Introduction
Today rapid changes are increase problems in agriculture sector and making decision more difficult. Problems that arise in real life have mostly complex structures and depend on several criteria’s and alternative. Therefore, multi-criteria and fuzzy TOPSIS decision-making techniques are used to study took into account the criteria set by decision-makers and evaluated in order to identify the most appropriate one Kargi, (2016). (Nădăban et al., 2016) have focused an overview of the development of TOPSIS fuzzy techniques. (Shamsuzzoha & Shamsuzzaman, 2021) have proposed a technique known as fuzzy technique in order to preferences based on similarity with the ideal solution (fuzzy TOPSIS) for the selections of complex projects in organizations. Ding, (2011) have purposed to develop an integrated fuzzy method for order-by-similarity preferences to the ideal solutions method (TOPSIS) in order to improve the quality of decision-making for the classification of alternatives. (Ertuğrul & Karakaşoğlu, 2007) have used fuzzy TOPSIS method for the preference of order by similarity to the ideal solution method of selection of academic members. a multi-criteria fuzzy group decision problem with the order implementation technique by similarity to the ideal solution (TOPSIS) base on the new idea of positive and negative ideal solutions (Javadian et al., 2009). (Husin et al., 2019) have identified a fuzzy TOPSIS technique connecting linguistics data is planned to confine vague condition. (Sevkli et al., 2010) have studied to evaluate and contrast crisp and fuzzy TOPSIS technique for the selection of suppliers selection. Aliyeva, (2018) have used multi-criteria fuzzy decision making with TOPSIS and Weighted Product Methods (WP) to choose the best locations for the company premises. (Adeyanju & Adedeji, 2017) have used Hybrid Fuzzy-Topsis method for Decision Making in Dam location Selections. (Sahin et al., 2020) have focused on purchasing decisions for dry bulk carriers on the basis of a multi-criteria decision analysis algorithm Fuzzy method for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). Irvanizam, (2018) have used Fuzzy TOPSIS to order the alternatives in descending order according to their relative proximity to the ideal solution. A fuzzy TOPSIS-based, multi-criteria decision-making technique is then planned to analyze and prioritize the most critical failure mode known by the FMEA study (Kolios et al., 2017). (Erdoğan et al., 2013) have proposed a hybrid methodology consisting of the SERVQUAL (Quality of Service) method, which categorizes the evaluation criteria, and the fuzzy TOPSIS (technique for order preference based on the similarity to the ideal solution) method, the alternatives for evaluating the quality of the service in PTS. (Ariapour et al., 2014) have purposed to develop fuzzy TOPSIS technique to improve the quality of decision making for variety of selection. Basahel, A., & Taylan, O. (2016) the fuzzy AHP technique was used to resolve the weighting of the criterion. Alternatively, a fuzzy method was used for the Order Performance by Similarity to Ideal Solution (TOPSIS) to estimate the performance of companies and to classify them according to their security performance. (Cezar-Vaz et al., 2015) have to investigated the relation between mental disorders, physical discomfort, house work and farm work between women. Mental Stress is a typical emotional response to unusually high demands in life. Everyone experience it; though, the result varies in intensity. There are several symptoms or sign of stress when a person needs help. These signs can be seen by family, friends, neighbours, school staff, or health and social services workers. (Padhy & Raju, 2018). (Hagen et al., 2019) have found the mental health problems among farmers are identified as population health problems. (Daghagh et al., 2019) have presented a systematic overview of the results, location, study design and technique of current studies on the mental health of farmers.