Agricultural Model for Allocation of Crops Using Pollination Intelligence Method. (1st June 2020)

• Record Type: Journal Article
• Authors: Ejieji, C. N.; Akinsunmade, A. E.
• Other Names: Dawson Christian W. Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2020(2020)
• Publication Date: 2020-06-01
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2020/4830359
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : An agricultural model for allocation of crops is considered in this work using Pollination Intelligence Method. The model was constructed to solve farmer's decision making in allocating crops to a piece of land using market price, known yield of crops, cost incurred during planting, and the total amount of land available. A new class of metaheuristic method called Flower Pollinated Algorithm is also presented in this work to solve the designed model. An improved version of the Flower Pollinated Algorithm called Pollination Intelligence Algorithm using an iterative scheme to override the switch parameter in Flower Pollinated Algorithm is also presented and used in solving the designed model. A case study of a farmer in Ife, Osun State, Nigeria, was used to implement the model, and the results obtained suggested that instead of allocating crops to land randomly based on farmer's intuition, cost of planting, yield of crops, and market price were factors that must be considered by farmers for optimal profit before planting crops.