Multiobjective Optimization of Crop-mix Planning Us ing Generalized Differential Evolution Algorithm

Abstract

This paper presents a model for constrained multiob jective optimization of mixed- cropping planning. The decision challenges that are normally faced by farmers include what to plant, when to plant, where to plant and ho w much to plant in order to yield maximum output. Consequently, the central objective of this work is to concurrently maximize net profit, maximize crop production and m inimize planting area. For this purpose, the generalized differential evolution 3 a lgorithm was explored to implement the mixed-cropping planning model, which was tested wit h data from the South African grain information service and the South African abstract of agricultural statistics. Simulation experiments were conducted using the non-dominated sorting genetic algorithm II to validate the performance of the generalized differe ntial evolution 3 algorithm. The empirical findings of this study indicated that gen eralized differential evolution 3 algorithm is a feasible optimization tool for solvi ng optimal mixed-cropping planning problems. Keywords: Cropping Pattern, Evolution, Genetics, Op timization, Planning.