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.
