Allocation of Agricultural Land for Optimal Crop Pattern Using Hybrid Flower Pollination-Dragonfly Method

Abstract

Allocation of agricultural land for optimal crop pattern is considered in this work. A mathematical model was constructed as a sensitizing tool in the agricultural sector to meet food demand and increase net production value of major crops grown in the country using data for known yield of crops, cost incurred during planting, total amount of land available and food production target. Two new classes of metaheuristic methods of optimization called Dragonfly Algorithm and Flower Pollination Algorithm are also presented in this work to solve the designed model. A new class of hybrid metaheuristic method combining the abilities of Flower Pollination
Algorithm and Dragonfly Algorithm called Hybrid Flower Pollination-Dragonfly Method is also constructed and used in solving the designed model. A case study of the Nigerian agricultural sector was used to implement the model. A net production value of $31,934,937,026.00 was obtained using the designed model to allocate crops as against the initial net production value of $23,130,563,800.00 recorded by the agricultural sector in the year 2016. Results obtained also suggest that cost of planting, yield of crops, market price, food production target and land allocation are important factors to be considered for optimal profit before planting crops.