Application of TOPSIS method in selection of design attributes of decision support system for fertilizer recommendation

Abstract

The selection of the most suitable design attributes out of available alternatives is usually remains a tedious and time-consuming task for designers. Due to complex design specifications and availability of multiple design alternatives of agricultural decision support systems for fertilizer prescriptions, the selection of design attributes is generally seen to be a multi-criterion decision-making problem. From the designer’s perspective, it is very important to build a decision model that helps in the identification and selection of the most suitable design attributes by using some standard, faster, and more objective methodology. To meet this objective, this paper presents a decision model to select the design attributes for the futuristic intelligent fertilizer recommendation system (IFRS) using the TOPSIS approach. The model first identifies the various design aspects and criteria as inputs for the TOPSIS method through a detailed study of existing DSS cum FRS. By using the identified criteria, a few of the state of art selected FRS are ranked and prioritize in order of preference by applying the TOPSIS approach. The ensemble of design attributes of the top-ranked FRS such as data inputs development technologies and support delivery methods are chosen as design specifications for futuristic IFRS. The author believes that the presented decision model will help the designers in the selection of design attributes and proposal of futuristic IFRS design.

Subject Classification:

• 91B06
• 68U35

Keywords:

• Design Criteria
• Decision Support System (DSS)
• Fertilizer Recommendation
• TOPSIS
• MCDM