Studies in swarm intelligence techniques for annual crop planning problem in a new irrigation scheme

Authors

  • Aderemi Oluyinka Adewumi School of Mathematics, Statistics and Computer Science University of Kwa-Zulu Natal University Road, Westville Private Bag X 54001, Durban, 4000, South Africa
  • Sivashan Chetty School of Mathematics, Statistics and Computer Science University of Kwa-Zulu Natal University Road, Westville Private Bag X 54001, Durban, 4000, South Africa

DOI:

https://doi.org/10.7166/24-3-626

Keywords:

Annual Crop Planning, Irrigated Water Requirements, Optimization, Cuckoo Search, Firefly Algorithm, Glowworm Swarm Optimization, Genetic Algorithm

Abstract

Annual crop planning (ACP) is an NP-Hard type optimisation problem in agricultural planning. It involves finding optimal solutions for the seasonal allocations of a limited amount of agricultural land among the various competing crops that need to be grown on it. This study investigates the effectiveness of employing three relatively new Swarm Intelligence (SI) techniques in determining solutions to an ACP problem at a new irrigation scheme. The SI metaheuristics studied include Cuckoo Search (CS), Firefly Algorithm (FA), and Glow-worm Swarm Optimisation (GSO). The solutions determined by these SI techniques are compared against the solutions of Genetic Algorithm (GA), another population-based metaheuristic technique. This helps to determine the relative merits of the solutions found by the SI techniques. The results show that the SI algorithms delivered solutions superior to those of GA in determining solutions to the ACP problem at a new irrigation scheme.

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Author Biography

Aderemi Oluyinka Adewumi, School of Mathematics, Statistics and Computer Science University of Kwa-Zulu Natal University Road, Westville Private Bag X 54001, Durban, 4000, South Africa

Aderemi Adewumi graduated and received the B.Sc. and M.Sc. degree in Computer Science from the University of Lagos, Nigeria. He received his PhD in Computational & Applied Mathematics from the University of Witwatersrand, South Africa with specialty in Optimization and Computational Intelligence. He currently leads the Optimization and Modeling research Group in the School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, South Africa. His research interests include optimization and artificial intelligence, with particular interest in computational intelligence and (meta) heuristics solutions to real-world global optimization problems.

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Published

2013-11-30

How to Cite

Adewumi, A. O., & Chetty, S. (2013). Studies in swarm intelligence techniques for annual crop planning problem in a new irrigation scheme. The South African Journal of Industrial Engineering, 24(3), 205–226. https://doi.org/10.7166/24-3-626

Issue

Vol. 24 No. 3 (2013)

Section

Case Studies

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