Comparison Study of Swarm Intelligence Techniques for the Annual Crop Planning Problem

Annual crop planning (ACP) is an NP-hard type optimization problem in agricultural planning. It involves finding the optimal solution for the seasonal hectare allocations of a limited amount of agricultural land, among various competing crops that are required to be grown on it. This study investigates the effectiveness of employing three relatively new swarm intelligence (SI) metaheuristic techniques in determining the solutions to the ACP problem with case study from an existing irrigation scheme. The SI metaheuristics studied are cuckoo search (CS), firefly algorithm (FA), and glowworm swarm optimization (GSO). Solutions obtained from these techniques are compared with that of a similar population-based technique, namely, genetic algorithm (GA). Results obtained show that each of the three SI algorithms provides superior solutions for the case studied.