Multi-objective optimization based decision-making process and its application to optimally select suitable greenhouse site for tomato crops

¹ Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103, India
² Department of Engineering Science, Academy of Technology, Adisaptagram, Krishnapur-Chandanpur, Hooghly 712502, India

^* Corresponding author: salam@math.iiests.ac.in; salam50in@yahoo.co.in

Received: 7 February 2024
Accepted: 27 September 2024

Abstract

In the modern agricultural system, the necessity for greenhouses is increasingly demanding due to unfavorable climatic conditions that hugely impact crop yields. The production of essential but very much weather-sensitive crops like tomatoes, beans, etc, can be improved by considering a greenhouse environment by regulating temperature, humidity, etc. In West Bengal’s lush plains tomato production has not been able to keep up with the growing demand, and prices for tomatoes in the state’s major cities have increased significantly in the recent past. However, designing the ideal greenhouse entails some ambiguity and complexity, given the variability in the climatic patterns and crop requirements. This uncertainty can be efficiently examined utilizing cylindrical neutrosophic set (CNS), which helps to manage the ambiguous and contradictory information inherent in decision-making processes, resulting in more exact and reliable greenhouse planning. Furthermore, the Dombi logarithmic law produces a very strong and consistent output result with a slight variation in operating parameters. In this research article, we have applied our proposed decision-making process to determine the best greenhouse site for cultivating tomato crops. For this purpose, we have defined Dombi logarithmic aggregation operational laws in the framework of cylindrical neutrosophic numbers (CNN) and utilized these laws to establish a new aggregation operator namely cylindrical neutrosophic Dombi weighted logarithmic aggregation operator (CNDWLA). The said aggregation operational laws & aggregation operator have been applied to present a new and novel decision-making process where full consistency method (FUCOM) and multi-objective optimization (MOO) have been integrated and embedded fruitfully. Here, the objective functions were formulated using the concept of a single-layer neural network and then MOO and FUCOM methods are implemented to assess criterion weights. We have resolved the most favorable pareto optimal solution derived from MOO by employing simulation and the method for order of preference by similarity to ideal solution (TOPSIS) approach. We also discovered that measurement alternatives and ranking according to compromise solution (MARCOS) and the multi-objective optimization on the basis of ratio analysis (MOORA) methods have not been utilized in the CN environment. Therefore, we have applied our proposed decision-making method with MARCOS and MOORA techniques to determine the optimal greenhouse site for tomato production in West Bengal. An exhaustive sensitivity and comparison analysis have been conducted to assess the stability and robustness of our multi-criteria group decision-making (MCGDM) method. The analysis of our study points out that South Bengal is the most appropriate greenhouse place for cultivating tomatoes in West Bengal.