Ontology-based knowledge and optimization model for Decision Support System to intercropping

Agriculture is one of the most significant domains in need of knowledge sharing and Decision Support Systems (DSS) that can help farmers make decisions to solve complex problems. Monoculture agriculture has many problems such as plant disease dramatically decreasing product price. Intercropping is an alternative way to reduce a risk of market price and plant disease. This research proposes three research objectives: (1) To determine the knowledge domain of intercropping planning system, (2) To develop an ontology-based knowledge prototype aimed at addressing the DSS of the planning intercropping system, and (3) To design an optimization model used for decision-making for the intercropping system. In this paper we present the ontology-based knowledge and multi-objective obtimization model to drive the decision support system for intercropping based on constraint factors from an individual farmer for illustrating maximum income and minimizing the cost for cultivating the plants.