Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors

Aderemi Oluyinka Adewumi; Sivashan Chetty

doi:10.1371/journal.pone.0180813

Investigating the enhanced Best Performance Algorithm for Annual Crop Planning problem based on economic factors

PLoS One. 2017 Aug 8;12(8):e0180813. doi: 10.1371/journal.pone.0180813. eCollection 2017.

Authors

Aderemi Oluyinka Adewumi¹, Sivashan Chetty¹

Affiliation

¹ School of Mathematics, Statistics and Computer Science, University of Kwa-Zulu Natal, Durban, South Africa.

Abstract

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA's results are compared against two well-known local search metaheuristic algorithms; these include Tabu Search and Simulated Annealing. The results show the potential of the eBPA for continuous optimization problems.

MeSH terms

Agricultural Irrigation / economics*
Algorithms*
Computer Simulation
Crop Production / economics*
Datasets as Topic
Models, Theoretical
Natural Resources
Rain
South Africa
Time Factors

Grants and funding

The financial assistance of the National Research Foundation (DAAD-NRF) towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at are those of the authors and are not necessarily to be attributed to the DAAD-NRF.